diff --git a/breast/ml/combination_5_fold.ipynb b/breast/ml/combination_5_fold.ipynb
new file mode 100644
index 0000000..eaf1c47
--- /dev/null
+++ b/breast/ml/combination_5_fold.ipynb
@@ -0,0 +1,5123 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 850k GSE237036"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
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+       "  </tbody>\n",
+       "</table>\n",
+       "<p>722696 rows × 161 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
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+       "3       cg14797042  0.935528  0.935528  0.913968  0.913968  0.928262   \n",
+       "4       cg09838562  0.044716  0.044716  0.043590  0.043590  0.029264   \n",
+       "...            ...       ...       ...       ...       ...       ...   \n",
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+       "722695  cg12325588  0.012300  0.012300  0.016042  0.016042  0.001981   \n",
+       "\n",
+       "               6         7         8         9  ...       151       152  \\\n",
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+       "4       0.042800  0.042800  0.041302  0.041302  0.023060  0.023060  0.037469   \n",
+       "...          ...       ...       ...       ...       ...       ...       ...   \n",
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+       "722695  0.018168  0.018168  0.012496  0.012496  0.007423  0.007423  0.018230   \n",
+       "\n",
+       "             160  \n",
+       "0       0.928855  \n",
+       "1       0.944323  \n",
+       "2       0.037160  \n",
+       "3       0.923486  \n",
+       "4       0.037469  \n",
+       "...          ...  \n",
+       "722691  0.904917  \n",
+       "722692  0.010832  \n",
+       "722693  0.019415  \n",
+       "722694  0.952388  \n",
+       "722695  0.018230  \n",
+       "\n",
+       "[722696 rows x 161 columns]"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd \n",
+    "import numpy as np\n",
+    "\n",
+    "df_beta_train = pd.read_csv(\"source/GSE237036/all_beta_normalized.csv\")\n",
+    "df_beta_train\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <td>0.943035</td>\n",
+       "      <td>0.928695</td>\n",
+       "      <td>0.928695</td>\n",
+       "      <td>0.941790</td>\n",
+       "      <td>0.941790</td>\n",
+       "      <td>0.954223</td>\n",
+       "      <td>0.954223</td>\n",
+       "      <td>0.964751</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.936065</td>\n",
+       "      <td>0.936065</td>\n",
+       "      <td>0.913382</td>\n",
+       "      <td>0.913382</td>\n",
+       "      <td>0.938807</td>\n",
+       "      <td>0.938807</td>\n",
+       "      <td>0.902528</td>\n",
+       "      <td>0.902528</td>\n",
+       "      <td>0.928855</td>\n",
+       "      <td>0.928855</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg03513874</td>\n",
+       "      <td>0.972519</td>\n",
+       "      <td>0.972519</td>\n",
+       "      <td>0.959357</td>\n",
+       "      <td>0.959357</td>\n",
+       "      <td>0.947300</td>\n",
+       "      <td>0.947300</td>\n",
+       "      <td>0.969835</td>\n",
+       "      <td>0.969835</td>\n",
+       "      <td>0.976845</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.956762</td>\n",
+       "      <td>0.956762</td>\n",
+       "      <td>0.962674</td>\n",
+       "      <td>0.962674</td>\n",
+       "      <td>0.951583</td>\n",
+       "      <td>0.951583</td>\n",
+       "      <td>0.956751</td>\n",
+       "      <td>0.956751</td>\n",
+       "      <td>0.944323</td>\n",
+       "      <td>0.944323</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg05451842</td>\n",
+       "      <td>0.021666</td>\n",
+       "      <td>0.021666</td>\n",
+       "      <td>0.021658</td>\n",
+       "      <td>0.021658</td>\n",
+       "      <td>0.014463</td>\n",
+       "      <td>0.014463</td>\n",
+       "      <td>0.010813</td>\n",
+       "      <td>0.010813</td>\n",
+       "      <td>0.018068</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.016141</td>\n",
+       "      <td>0.016141</td>\n",
+       "      <td>0.028114</td>\n",
+       "      <td>0.028114</td>\n",
+       "      <td>0.014931</td>\n",
+       "      <td>0.014931</td>\n",
+       "      <td>0.016914</td>\n",
+       "      <td>0.016914</td>\n",
+       "      <td>0.037160</td>\n",
+       "      <td>0.037160</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg14797042</td>\n",
+       "      <td>0.935528</td>\n",
+       "      <td>0.935528</td>\n",
+       "      <td>0.913968</td>\n",
+       "      <td>0.913968</td>\n",
+       "      <td>0.928262</td>\n",
+       "      <td>0.928262</td>\n",
+       "      <td>0.902112</td>\n",
+       "      <td>0.902112</td>\n",
+       "      <td>0.907727</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.905364</td>\n",
+       "      <td>0.905364</td>\n",
+       "      <td>0.922666</td>\n",
+       "      <td>0.922666</td>\n",
+       "      <td>0.931447</td>\n",
+       "      <td>0.931447</td>\n",
+       "      <td>0.911759</td>\n",
+       "      <td>0.911759</td>\n",
+       "      <td>0.923486</td>\n",
+       "      <td>0.923486</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg09838562</td>\n",
+       "      <td>0.044716</td>\n",
+       "      <td>0.044716</td>\n",
+       "      <td>0.043590</td>\n",
+       "      <td>0.043590</td>\n",
+       "      <td>0.029264</td>\n",
+       "      <td>0.029264</td>\n",
+       "      <td>0.043756</td>\n",
+       "      <td>0.043756</td>\n",
+       "      <td>0.064916</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.038566</td>\n",
+       "      <td>0.038566</td>\n",
+       "      <td>0.042800</td>\n",
+       "      <td>0.042800</td>\n",
+       "      <td>0.041302</td>\n",
+       "      <td>0.041302</td>\n",
+       "      <td>0.023060</td>\n",
+       "      <td>0.023060</td>\n",
+       "      <td>0.037469</td>\n",
+       "      <td>0.037469</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>722691</th>\n",
+       "      <td>cg19812938</td>\n",
+       "      <td>0.912999</td>\n",
+       "      <td>0.912999</td>\n",
+       "      <td>0.891436</td>\n",
+       "      <td>0.891436</td>\n",
+       "      <td>0.916324</td>\n",
+       "      <td>0.916324</td>\n",
+       "      <td>0.908014</td>\n",
+       "      <td>0.908014</td>\n",
+       "      <td>0.909659</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.898839</td>\n",
+       "      <td>0.898839</td>\n",
+       "      <td>0.913186</td>\n",
+       "      <td>0.913186</td>\n",
+       "      <td>0.897586</td>\n",
+       "      <td>0.897586</td>\n",
+       "      <td>0.902874</td>\n",
+       "      <td>0.902874</td>\n",
+       "      <td>0.904917</td>\n",
+       "      <td>0.904917</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>722692</th>\n",
+       "      <td>cg06272054</td>\n",
+       "      <td>0.007895</td>\n",
+       "      <td>0.007895</td>\n",
+       "      <td>0.015901</td>\n",
+       "      <td>0.015901</td>\n",
+       "      <td>0.005838</td>\n",
+       "      <td>0.005838</td>\n",
+       "      <td>0.003103</td>\n",
+       "      <td>0.003103</td>\n",
+       "      <td>0.011144</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.009814</td>\n",
+       "      <td>0.009814</td>\n",
+       "      <td>0.009527</td>\n",
+       "      <td>0.009527</td>\n",
+       "      <td>0.006864</td>\n",
+       "      <td>0.006864</td>\n",
+       "      <td>0.010792</td>\n",
+       "      <td>0.010792</td>\n",
+       "      <td>0.010832</td>\n",
+       "      <td>0.010832</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>722693</th>\n",
+       "      <td>cg07255356</td>\n",
+       "      <td>0.022079</td>\n",
+       "      <td>0.022079</td>\n",
+       "      <td>0.003488</td>\n",
+       "      <td>0.003488</td>\n",
+       "      <td>0.006069</td>\n",
+       "      <td>0.006069</td>\n",
+       "      <td>0.007304</td>\n",
+       "      <td>0.007304</td>\n",
+       "      <td>0.013703</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.007952</td>\n",
+       "      <td>0.007952</td>\n",
+       "      <td>0.013918</td>\n",
+       "      <td>0.013918</td>\n",
+       "      <td>0.023236</td>\n",
+       "      <td>0.023236</td>\n",
+       "      <td>0.021588</td>\n",
+       "      <td>0.021588</td>\n",
+       "      <td>0.019415</td>\n",
+       "      <td>0.019415</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>722694</th>\n",
+       "      <td>cg24220897</td>\n",
+       "      <td>0.957847</td>\n",
+       "      <td>0.957847</td>\n",
+       "      <td>0.941408</td>\n",
+       "      <td>0.941408</td>\n",
+       "      <td>0.948018</td>\n",
+       "      <td>0.948018</td>\n",
+       "      <td>0.963731</td>\n",
+       "      <td>0.963731</td>\n",
+       "      <td>0.979047</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.948178</td>\n",
+       "      <td>0.948178</td>\n",
+       "      <td>0.952919</td>\n",
+       "      <td>0.952919</td>\n",
+       "      <td>0.928063</td>\n",
+       "      <td>0.928063</td>\n",
+       "      <td>0.991733</td>\n",
+       "      <td>0.991733</td>\n",
+       "      <td>0.952388</td>\n",
+       "      <td>0.952388</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>722695</th>\n",
+       "      <td>cg12325588</td>\n",
+       "      <td>0.012300</td>\n",
+       "      <td>0.012300</td>\n",
+       "      <td>0.016042</td>\n",
+       "      <td>0.016042</td>\n",
+       "      <td>0.001981</td>\n",
+       "      <td>0.001981</td>\n",
+       "      <td>0.006149</td>\n",
+       "      <td>0.006149</td>\n",
+       "      <td>0.009990</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.007574</td>\n",
+       "      <td>0.007574</td>\n",
+       "      <td>0.018168</td>\n",
+       "      <td>0.018168</td>\n",
+       "      <td>0.012496</td>\n",
+       "      <td>0.012496</td>\n",
+       "      <td>0.007423</td>\n",
+       "      <td>0.007423</td>\n",
+       "      <td>0.018230</td>\n",
+       "      <td>0.018230</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>722696 rows × 161 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unnamed: 0         1         2         3         4         5  \\\n",
+       "0       cg07881041  0.943035  0.943035  0.928695  0.928695  0.941790   \n",
+       "1       cg03513874  0.972519  0.972519  0.959357  0.959357  0.947300   \n",
+       "2       cg05451842  0.021666  0.021666  0.021658  0.021658  0.014463   \n",
+       "3       cg14797042  0.935528  0.935528  0.913968  0.913968  0.928262   \n",
+       "4       cg09838562  0.044716  0.044716  0.043590  0.043590  0.029264   \n",
+       "...            ...       ...       ...       ...       ...       ...   \n",
+       "722691  cg19812938  0.912999  0.912999  0.891436  0.891436  0.916324   \n",
+       "722692  cg06272054  0.007895  0.007895  0.015901  0.015901  0.005838   \n",
+       "722693  cg07255356  0.022079  0.022079  0.003488  0.003488  0.006069   \n",
+       "722694  cg24220897  0.957847  0.957847  0.941408  0.941408  0.948018   \n",
+       "722695  cg12325588  0.012300  0.012300  0.016042  0.016042  0.001981   \n",
+       "\n",
+       "               6         7         8         9  ...       151       152  \\\n",
+       "0       0.941790  0.954223  0.954223  0.964751  ...  0.936065  0.936065   \n",
+       "1       0.947300  0.969835  0.969835  0.976845  ...  0.956762  0.956762   \n",
+       "2       0.014463  0.010813  0.010813  0.018068  ...  0.016141  0.016141   \n",
+       "3       0.928262  0.902112  0.902112  0.907727  ...  0.905364  0.905364   \n",
+       "4       0.029264  0.043756  0.043756  0.064916  ...  0.038566  0.038566   \n",
+       "...          ...       ...       ...       ...  ...       ...       ...   \n",
+       "722691  0.916324  0.908014  0.908014  0.909659  ...  0.898839  0.898839   \n",
+       "722692  0.005838  0.003103  0.003103  0.011144  ...  0.009814  0.009814   \n",
+       "722693  0.006069  0.007304  0.007304  0.013703  ...  0.007952  0.007952   \n",
+       "722694  0.948018  0.963731  0.963731  0.979047  ...  0.948178  0.948178   \n",
+       "722695  0.001981  0.006149  0.006149  0.009990  ...  0.007574  0.007574   \n",
+       "\n",
+       "             153       154       155       156       157       158       159  \\\n",
+       "0       0.913382  0.913382  0.938807  0.938807  0.902528  0.902528  0.928855   \n",
+       "1       0.962674  0.962674  0.951583  0.951583  0.956751  0.956751  0.944323   \n",
+       "2       0.028114  0.028114  0.014931  0.014931  0.016914  0.016914  0.037160   \n",
+       "3       0.922666  0.922666  0.931447  0.931447  0.911759  0.911759  0.923486   \n",
+       "4       0.042800  0.042800  0.041302  0.041302  0.023060  0.023060  0.037469   \n",
+       "...          ...       ...       ...       ...       ...       ...       ...   \n",
+       "722691  0.913186  0.913186  0.897586  0.897586  0.902874  0.902874  0.904917   \n",
+       "722692  0.009527  0.009527  0.006864  0.006864  0.010792  0.010792  0.010832   \n",
+       "722693  0.013918  0.013918  0.023236  0.023236  0.021588  0.021588  0.019415   \n",
+       "722694  0.952919  0.952919  0.928063  0.928063  0.991733  0.991733  0.952388   \n",
+       "722695  0.018168  0.018168  0.012496  0.012496  0.007423  0.007423  0.018230   \n",
+       "\n",
+       "             160  \n",
+       "0       0.928855  \n",
+       "1       0.944323  \n",
+       "2       0.037160  \n",
+       "3       0.923486  \n",
+       "4       0.037469  \n",
+       "...          ...  \n",
+       "722691  0.904917  \n",
+       "722692  0.010832  \n",
+       "722693  0.019415  \n",
+       "722694  0.952388  \n",
+       "722695  0.018230  \n",
+       "\n",
+       "[722696 rows x 161 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_mix_train = df_beta_train\n",
+    "df_mix_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>cg07881041</th>\n",
+       "      <th>cg03513874</th>\n",
+       "      <th>cg05451842</th>\n",
+       "      <th>cg14797042</th>\n",
+       "      <th>cg09838562</th>\n",
+       "      <th>cg25458538</th>\n",
+       "      <th>cg09261072</th>\n",
+       "      <th>cg02404579</th>\n",
+       "      <th>cg04118974</th>\n",
+       "      <th>cg01236347</th>\n",
+       "      <th>...</th>\n",
+       "      <th>cg23020486</th>\n",
+       "      <th>cg10295858</th>\n",
+       "      <th>cg11606463</th>\n",
+       "      <th>cg04767756</th>\n",
+       "      <th>cg05166473</th>\n",
+       "      <th>cg19812938</th>\n",
+       "      <th>cg06272054</th>\n",
+       "      <th>cg07255356</th>\n",
+       "      <th>cg24220897</th>\n",
+       "      <th>cg12325588</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.943035</td>\n",
+       "      <td>0.972519</td>\n",
+       "      <td>0.021666</td>\n",
+       "      <td>0.935528</td>\n",
+       "      <td>0.044716</td>\n",
+       "      <td>0.844793</td>\n",
+       "      <td>0.571696</td>\n",
+       "      <td>0.827540</td>\n",
+       "      <td>0.639979</td>\n",
+       "      <td>0.659230</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.060316</td>\n",
+       "      <td>0.941576</td>\n",
+       "      <td>0.956549</td>\n",
+       "      <td>0.971737</td>\n",
+       "      <td>0.860206</td>\n",
+       "      <td>0.912999</td>\n",
+       "      <td>0.007895</td>\n",
+       "      <td>0.022079</td>\n",
+       "      <td>0.957847</td>\n",
+       "      <td>0.012300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.928695</td>\n",
+       "      <td>0.959357</td>\n",
+       "      <td>0.021658</td>\n",
+       "      <td>0.913968</td>\n",
+       "      <td>0.043590</td>\n",
+       "      <td>0.872192</td>\n",
+       "      <td>0.502146</td>\n",
+       "      <td>0.879208</td>\n",
+       "      <td>0.776555</td>\n",
+       "      <td>0.714857</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.030365</td>\n",
+       "      <td>0.939998</td>\n",
+       "      <td>0.965705</td>\n",
+       "      <td>0.973995</td>\n",
+       "      <td>0.802455</td>\n",
+       "      <td>0.891436</td>\n",
+       "      <td>0.015901</td>\n",
+       "      <td>0.003488</td>\n",
+       "      <td>0.941408</td>\n",
+       "      <td>0.016042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>0.941790</td>\n",
+       "      <td>0.947300</td>\n",
+       "      <td>0.014463</td>\n",
+       "      <td>0.928262</td>\n",
+       "      <td>0.029264</td>\n",
+       "      <td>0.897742</td>\n",
+       "      <td>0.604268</td>\n",
+       "      <td>0.869354</td>\n",
+       "      <td>0.738219</td>\n",
+       "      <td>0.708490</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.017773</td>\n",
+       "      <td>0.944872</td>\n",
+       "      <td>0.953891</td>\n",
+       "      <td>0.970152</td>\n",
+       "      <td>0.818088</td>\n",
+       "      <td>0.916324</td>\n",
+       "      <td>0.005838</td>\n",
+       "      <td>0.006069</td>\n",
+       "      <td>0.948018</td>\n",
+       "      <td>0.001981</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0.954223</td>\n",
+       "      <td>0.969835</td>\n",
+       "      <td>0.010813</td>\n",
+       "      <td>0.902112</td>\n",
+       "      <td>0.043756</td>\n",
+       "      <td>0.891614</td>\n",
+       "      <td>0.627630</td>\n",
+       "      <td>0.818216</td>\n",
+       "      <td>0.667162</td>\n",
+       "      <td>0.650270</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.009691</td>\n",
+       "      <td>0.972959</td>\n",
+       "      <td>0.969428</td>\n",
+       "      <td>0.974948</td>\n",
+       "      <td>0.868651</td>\n",
+       "      <td>0.908014</td>\n",
+       "      <td>0.003103</td>\n",
+       "      <td>0.007304</td>\n",
+       "      <td>0.963731</td>\n",
+       "      <td>0.006149</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>0.964751</td>\n",
+       "      <td>0.976845</td>\n",
+       "      <td>0.018068</td>\n",
+       "      <td>0.907727</td>\n",
+       "      <td>0.064916</td>\n",
+       "      <td>0.918115</td>\n",
+       "      <td>0.682568</td>\n",
+       "      <td>0.867510</td>\n",
+       "      <td>0.667478</td>\n",
+       "      <td>0.613951</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.016076</td>\n",
+       "      <td>0.959985</td>\n",
+       "      <td>0.971484</td>\n",
+       "      <td>0.978449</td>\n",
+       "      <td>0.783682</td>\n",
+       "      <td>0.909659</td>\n",
+       "      <td>0.011144</td>\n",
+       "      <td>0.013703</td>\n",
+       "      <td>0.979047</td>\n",
+       "      <td>0.009990</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>151</th>\n",
+       "      <td>0.936065</td>\n",
+       "      <td>0.956762</td>\n",
+       "      <td>0.016141</td>\n",
+       "      <td>0.905364</td>\n",
+       "      <td>0.038566</td>\n",
+       "      <td>0.854424</td>\n",
+       "      <td>0.535792</td>\n",
+       "      <td>0.852040</td>\n",
+       "      <td>0.678075</td>\n",
+       "      <td>0.660842</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.015208</td>\n",
+       "      <td>0.949463</td>\n",
+       "      <td>0.957916</td>\n",
+       "      <td>0.972775</td>\n",
+       "      <td>0.853073</td>\n",
+       "      <td>0.898839</td>\n",
+       "      <td>0.009814</td>\n",
+       "      <td>0.007952</td>\n",
+       "      <td>0.948178</td>\n",
+       "      <td>0.007574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>153</th>\n",
+       "      <td>0.913382</td>\n",
+       "      <td>0.962674</td>\n",
+       "      <td>0.028114</td>\n",
+       "      <td>0.922666</td>\n",
+       "      <td>0.042800</td>\n",
+       "      <td>0.863198</td>\n",
+       "      <td>0.553173</td>\n",
+       "      <td>0.832280</td>\n",
+       "      <td>0.678828</td>\n",
+       "      <td>0.668299</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.009110</td>\n",
+       "      <td>0.952642</td>\n",
+       "      <td>0.961514</td>\n",
+       "      <td>0.987125</td>\n",
+       "      <td>0.864020</td>\n",
+       "      <td>0.913186</td>\n",
+       "      <td>0.009527</td>\n",
+       "      <td>0.013918</td>\n",
+       "      <td>0.952919</td>\n",
+       "      <td>0.018168</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>155</th>\n",
+       "      <td>0.938807</td>\n",
+       "      <td>0.951583</td>\n",
+       "      <td>0.014931</td>\n",
+       "      <td>0.931447</td>\n",
+       "      <td>0.041302</td>\n",
+       "      <td>0.869738</td>\n",
+       "      <td>0.563984</td>\n",
+       "      <td>0.852718</td>\n",
+       "      <td>0.685830</td>\n",
+       "      <td>0.637114</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.026123</td>\n",
+       "      <td>0.949775</td>\n",
+       "      <td>0.977050</td>\n",
+       "      <td>0.972949</td>\n",
+       "      <td>0.836172</td>\n",
+       "      <td>0.897586</td>\n",
+       "      <td>0.006864</td>\n",
+       "      <td>0.023236</td>\n",
+       "      <td>0.928063</td>\n",
+       "      <td>0.012496</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>157</th>\n",
+       "      <td>0.902528</td>\n",
+       "      <td>0.956751</td>\n",
+       "      <td>0.016914</td>\n",
+       "      <td>0.911759</td>\n",
+       "      <td>0.023060</td>\n",
+       "      <td>0.858436</td>\n",
+       "      <td>0.598913</td>\n",
+       "      <td>0.850269</td>\n",
+       "      <td>0.714154</td>\n",
+       "      <td>0.650321</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.009521</td>\n",
+       "      <td>0.956029</td>\n",
+       "      <td>0.961933</td>\n",
+       "      <td>0.973431</td>\n",
+       "      <td>0.812455</td>\n",
+       "      <td>0.902874</td>\n",
+       "      <td>0.010792</td>\n",
+       "      <td>0.021588</td>\n",
+       "      <td>0.991733</td>\n",
+       "      <td>0.007423</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>159</th>\n",
+       "      <td>0.928855</td>\n",
+       "      <td>0.944323</td>\n",
+       "      <td>0.037160</td>\n",
+       "      <td>0.923486</td>\n",
+       "      <td>0.037469</td>\n",
+       "      <td>0.875550</td>\n",
+       "      <td>0.599773</td>\n",
+       "      <td>0.792722</td>\n",
+       "      <td>0.669537</td>\n",
+       "      <td>0.687345</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014288</td>\n",
+       "      <td>0.947310</td>\n",
+       "      <td>0.967683</td>\n",
+       "      <td>0.974959</td>\n",
+       "      <td>0.888935</td>\n",
+       "      <td>0.904917</td>\n",
+       "      <td>0.010832</td>\n",
+       "      <td>0.019415</td>\n",
+       "      <td>0.952388</td>\n",
+       "      <td>0.018230</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>80 rows × 722696 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Unnamed: 0  cg07881041  cg03513874  cg05451842  cg14797042  cg09838562  \\\n",
+       "1             0.943035    0.972519    0.021666    0.935528    0.044716   \n",
+       "3             0.928695    0.959357    0.021658    0.913968    0.043590   \n",
+       "5             0.941790    0.947300    0.014463    0.928262    0.029264   \n",
+       "7             0.954223    0.969835    0.010813    0.902112    0.043756   \n",
+       "9             0.964751    0.976845    0.018068    0.907727    0.064916   \n",
+       "..                 ...         ...         ...         ...         ...   \n",
+       "151           0.936065    0.956762    0.016141    0.905364    0.038566   \n",
+       "153           0.913382    0.962674    0.028114    0.922666    0.042800   \n",
+       "155           0.938807    0.951583    0.014931    0.931447    0.041302   \n",
+       "157           0.902528    0.956751    0.016914    0.911759    0.023060   \n",
+       "159           0.928855    0.944323    0.037160    0.923486    0.037469   \n",
+       "\n",
+       "Unnamed: 0  cg25458538  cg09261072  cg02404579  cg04118974  cg01236347  ...  \\\n",
+       "1             0.844793    0.571696    0.827540    0.639979    0.659230  ...   \n",
+       "3             0.872192    0.502146    0.879208    0.776555    0.714857  ...   \n",
+       "5             0.897742    0.604268    0.869354    0.738219    0.708490  ...   \n",
+       "7             0.891614    0.627630    0.818216    0.667162    0.650270  ...   \n",
+       "9             0.918115    0.682568    0.867510    0.667478    0.613951  ...   \n",
+       "..                 ...         ...         ...         ...         ...  ...   \n",
+       "151           0.854424    0.535792    0.852040    0.678075    0.660842  ...   \n",
+       "153           0.863198    0.553173    0.832280    0.678828    0.668299  ...   \n",
+       "155           0.869738    0.563984    0.852718    0.685830    0.637114  ...   \n",
+       "157           0.858436    0.598913    0.850269    0.714154    0.650321  ...   \n",
+       "159           0.875550    0.599773    0.792722    0.669537    0.687345  ...   \n",
+       "\n",
+       "Unnamed: 0  cg23020486  cg10295858  cg11606463  cg04767756  cg05166473  \\\n",
+       "1             0.060316    0.941576    0.956549    0.971737    0.860206   \n",
+       "3             0.030365    0.939998    0.965705    0.973995    0.802455   \n",
+       "5             0.017773    0.944872    0.953891    0.970152    0.818088   \n",
+       "7             0.009691    0.972959    0.969428    0.974948    0.868651   \n",
+       "9             0.016076    0.959985    0.971484    0.978449    0.783682   \n",
+       "..                 ...         ...         ...         ...         ...   \n",
+       "151           0.015208    0.949463    0.957916    0.972775    0.853073   \n",
+       "153           0.009110    0.952642    0.961514    0.987125    0.864020   \n",
+       "155           0.026123    0.949775    0.977050    0.972949    0.836172   \n",
+       "157           0.009521    0.956029    0.961933    0.973431    0.812455   \n",
+       "159           0.014288    0.947310    0.967683    0.974959    0.888935   \n",
+       "\n",
+       "Unnamed: 0  cg19812938  cg06272054  cg07255356  cg24220897  cg12325588  \n",
+       "1             0.912999    0.007895    0.022079    0.957847    0.012300  \n",
+       "3             0.891436    0.015901    0.003488    0.941408    0.016042  \n",
+       "5             0.916324    0.005838    0.006069    0.948018    0.001981  \n",
+       "7             0.908014    0.003103    0.007304    0.963731    0.006149  \n",
+       "9             0.909659    0.011144    0.013703    0.979047    0.009990  \n",
+       "..                 ...         ...         ...         ...         ...  \n",
+       "151           0.898839    0.009814    0.007952    0.948178    0.007574  \n",
+       "153           0.913186    0.009527    0.013918    0.952919    0.018168  \n",
+       "155           0.897586    0.006864    0.023236    0.928063    0.012496  \n",
+       "157           0.902874    0.010792    0.021588    0.991733    0.007423  \n",
+       "159           0.904917    0.010832    0.019415    0.952388    0.018230  \n",
+       "\n",
+       "[80 rows x 722696 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "df_mix_train.set_index(\"Unnamed: 0\", inplace=True)\n",
+    "df_mix_train\n",
+    "\n",
+    "df_mix_train = df_mix_train.iloc[:, ::2]\n",
+    "df_mix_train\n",
+    "\n",
+    "X_train = df_mix_train.T\n",
+    "\n",
+    "X_train_normal_count = 30\n",
+    "\n",
+    "if (X_train_normal_count):\n",
+    "    y_train = [(0 if i < (X_train_normal_count) else 1) for i in range(len(X_train))]\n",
+    "\n",
+    "X_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "訓練集類別分佈:\n",
+      "   Class  Count  Percentage\n",
+      "0      0     23     35.9375\n",
+      "1      1     41     64.0625\n",
+      "\n",
+      "測試集類別分佈:\n",
+      "   Class  Count  Percentage\n",
+      "0      0      7       43.75\n",
+      "1      1      9       56.25\n",
+      "\n",
+      "訓練集和測試集的大小:\n",
+      "訓練集大小: 64\n",
+      "測試集大小: 16\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>cg07881041</th>\n",
+       "      <th>cg03513874</th>\n",
+       "      <th>cg05451842</th>\n",
+       "      <th>cg14797042</th>\n",
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+       "      <th>cg25458538</th>\n",
+       "      <th>cg09261072</th>\n",
+       "      <th>cg02404579</th>\n",
+       "      <th>cg04118974</th>\n",
+       "      <th>cg01236347</th>\n",
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+       "      <th>cg23020486</th>\n",
+       "      <th>cg10295858</th>\n",
+       "      <th>cg11606463</th>\n",
+       "      <th>cg04767756</th>\n",
+       "      <th>cg05166473</th>\n",
+       "      <th>cg19812938</th>\n",
+       "      <th>cg06272054</th>\n",
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+       "      <th>cg24220897</th>\n",
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+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>147</th>\n",
+       "      <td>0.929869</td>\n",
+       "      <td>0.937854</td>\n",
+       "      <td>0.025836</td>\n",
+       "      <td>0.923218</td>\n",
+       "      <td>0.039296</td>\n",
+       "      <td>0.874494</td>\n",
+       "      <td>0.580354</td>\n",
+       "      <td>0.848220</td>\n",
+       "      <td>0.732272</td>\n",
+       "      <td>0.729814</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.010867</td>\n",
+       "      <td>0.934795</td>\n",
+       "      <td>0.964980</td>\n",
+       "      <td>0.977291</td>\n",
+       "      <td>0.877755</td>\n",
+       "      <td>0.909622</td>\n",
+       "      <td>0.007554</td>\n",
+       "      <td>0.015903</td>\n",
+       "      <td>0.962175</td>\n",
+       "      <td>0.012816</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>123</th>\n",
+       "      <td>0.949800</td>\n",
+       "      <td>0.980382</td>\n",
+       "      <td>0.015201</td>\n",
+       "      <td>0.915660</td>\n",
+       "      <td>0.041336</td>\n",
+       "      <td>0.898642</td>\n",
+       "      <td>0.672970</td>\n",
+       "      <td>0.872005</td>\n",
+       "      <td>0.709339</td>\n",
+       "      <td>0.703964</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.006162</td>\n",
+       "      <td>0.955088</td>\n",
+       "      <td>0.967771</td>\n",
+       "      <td>0.973018</td>\n",
+       "      <td>0.871426</td>\n",
+       "      <td>0.910810</td>\n",
+       "      <td>0.001273</td>\n",
+       "      <td>0.004006</td>\n",
+       "      <td>0.964292</td>\n",
+       "      <td>0.004801</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111</th>\n",
+       "      <td>0.919833</td>\n",
+       "      <td>0.945657</td>\n",
+       "      <td>0.021001</td>\n",
+       "      <td>0.930932</td>\n",
+       "      <td>0.071066</td>\n",
+       "      <td>0.911834</td>\n",
+       "      <td>0.586978</td>\n",
+       "      <td>0.874440</td>\n",
+       "      <td>0.747679</td>\n",
+       "      <td>0.725431</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.003528</td>\n",
+       "      <td>0.950890</td>\n",
+       "      <td>0.956282</td>\n",
+       "      <td>0.962483</td>\n",
+       "      <td>0.838458</td>\n",
+       "      <td>0.919360</td>\n",
+       "      <td>0.010293</td>\n",
+       "      <td>0.013462</td>\n",
+       "      <td>0.967021</td>\n",
+       "      <td>0.019233</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>81</th>\n",
+       "      <td>0.933805</td>\n",
+       "      <td>0.958004</td>\n",
+       "      <td>0.028373</td>\n",
+       "      <td>0.908695</td>\n",
+       "      <td>0.053670</td>\n",
+       "      <td>0.860132</td>\n",
+       "      <td>0.559542</td>\n",
+       "      <td>0.810488</td>\n",
+       "      <td>0.662618</td>\n",
+       "      <td>0.601927</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.011977</td>\n",
+       "      <td>0.951810</td>\n",
+       "      <td>0.956689</td>\n",
+       "      <td>0.968849</td>\n",
+       "      <td>0.752360</td>\n",
+       "      <td>0.888231</td>\n",
+       "      <td>0.014288</td>\n",
+       "      <td>0.016157</td>\n",
+       "      <td>0.963459</td>\n",
+       "      <td>0.001869</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>0.937412</td>\n",
+       "      <td>0.977623</td>\n",
+       "      <td>0.035484</td>\n",
+       "      <td>0.914917</td>\n",
+       "      <td>0.062981</td>\n",
+       "      <td>0.889454</td>\n",
+       "      <td>0.614411</td>\n",
+       "      <td>0.840286</td>\n",
+       "      <td>0.732261</td>\n",
+       "      <td>0.719624</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.011912</td>\n",
+       "      <td>0.951209</td>\n",
+       "      <td>0.961675</td>\n",
+       "      <td>0.973922</td>\n",
+       "      <td>0.830171</td>\n",
+       "      <td>0.909684</td>\n",
+       "      <td>0.004134</td>\n",
+       "      <td>0.008814</td>\n",
+       "      <td>0.962250</td>\n",
+       "      <td>0.009267</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>0.953017</td>\n",
+       "      <td>0.963662</td>\n",
+       "      <td>0.020992</td>\n",
+       "      <td>0.919031</td>\n",
+       "      <td>0.038409</td>\n",
+       "      <td>0.907213</td>\n",
+       "      <td>0.648510</td>\n",
+       "      <td>0.864150</td>\n",
+       "      <td>0.632262</td>\n",
+       "      <td>0.634195</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.047900</td>\n",
+       "      <td>0.951220</td>\n",
+       "      <td>0.961997</td>\n",
+       "      <td>0.961776</td>\n",
+       "      <td>0.799364</td>\n",
+       "      <td>0.911416</td>\n",
+       "      <td>0.011963</td>\n",
+       "      <td>0.013717</td>\n",
+       "      <td>0.944111</td>\n",
+       "      <td>0.013061</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>0.949470</td>\n",
+       "      <td>0.954506</td>\n",
+       "      <td>0.026074</td>\n",
+       "      <td>0.926119</td>\n",
+       "      <td>0.041885</td>\n",
+       "      <td>0.907656</td>\n",
+       "      <td>0.590956</td>\n",
+       "      <td>0.853172</td>\n",
+       "      <td>0.770850</td>\n",
+       "      <td>0.777764</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.056822</td>\n",
+       "      <td>0.944244</td>\n",
+       "      <td>0.955128</td>\n",
+       "      <td>0.966364</td>\n",
+       "      <td>0.866610</td>\n",
+       "      <td>0.893951</td>\n",
+       "      <td>0.011442</td>\n",
+       "      <td>0.015364</td>\n",
+       "      <td>0.938603</td>\n",
+       "      <td>0.012846</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>143</th>\n",
+       "      <td>0.946295</td>\n",
+       "      <td>0.960032</td>\n",
+       "      <td>0.027482</td>\n",
+       "      <td>0.925875</td>\n",
+       "      <td>0.041850</td>\n",
+       "      <td>0.874872</td>\n",
+       "      <td>0.606528</td>\n",
+       "      <td>0.837673</td>\n",
+       "      <td>0.721731</td>\n",
+       "      <td>0.651609</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.009074</td>\n",
+       "      <td>0.951921</td>\n",
+       "      <td>0.965835</td>\n",
+       "      <td>0.968034</td>\n",
+       "      <td>0.824260</td>\n",
+       "      <td>0.893882</td>\n",
+       "      <td>0.015032</td>\n",
+       "      <td>0.008654</td>\n",
+       "      <td>0.967088</td>\n",
+       "      <td>0.009491</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>0.940191</td>\n",
+       "      <td>0.955949</td>\n",
+       "      <td>0.011189</td>\n",
+       "      <td>0.922794</td>\n",
+       "      <td>0.024096</td>\n",
+       "      <td>0.901456</td>\n",
+       "      <td>0.653031</td>\n",
+       "      <td>0.882988</td>\n",
+       "      <td>0.744746</td>\n",
+       "      <td>0.733421</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.002640</td>\n",
+       "      <td>0.963313</td>\n",
+       "      <td>0.968439</td>\n",
+       "      <td>0.969757</td>\n",
+       "      <td>0.876919</td>\n",
+       "      <td>0.903055</td>\n",
+       "      <td>0.008123</td>\n",
+       "      <td>0.009624</td>\n",
+       "      <td>0.977987</td>\n",
+       "      <td>0.002156</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>103</th>\n",
+       "      <td>0.940309</td>\n",
+       "      <td>0.977069</td>\n",
+       "      <td>0.021970</td>\n",
+       "      <td>0.911637</td>\n",
+       "      <td>0.028395</td>\n",
+       "      <td>0.873748</td>\n",
+       "      <td>0.547899</td>\n",
+       "      <td>0.819265</td>\n",
+       "      <td>0.689862</td>\n",
+       "      <td>0.643268</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.005453</td>\n",
+       "      <td>0.952067</td>\n",
+       "      <td>0.964782</td>\n",
+       "      <td>0.968374</td>\n",
+       "      <td>0.801423</td>\n",
+       "      <td>0.901259</td>\n",
+       "      <td>0.010529</td>\n",
+       "      <td>0.002935</td>\n",
+       "      <td>0.911680</td>\n",
+       "      <td>0.015609</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>64 rows × 722696 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Unnamed: 0  cg07881041  cg03513874  cg05451842  cg14797042  cg09838562  \\\n",
+       "147           0.929869    0.937854    0.025836    0.923218    0.039296   \n",
+       "123           0.949800    0.980382    0.015201    0.915660    0.041336   \n",
+       "111           0.919833    0.945657    0.021001    0.930932    0.071066   \n",
+       "81            0.933805    0.958004    0.028373    0.908695    0.053670   \n",
+       "19            0.937412    0.977623    0.035484    0.914917    0.062981   \n",
+       "..                 ...         ...         ...         ...         ...   \n",
+       "41            0.953017    0.963662    0.020992    0.919031    0.038409   \n",
+       "121           0.949470    0.954506    0.026074    0.926119    0.041885   \n",
+       "143           0.946295    0.960032    0.027482    0.925875    0.041850   \n",
+       "29            0.940191    0.955949    0.011189    0.922794    0.024096   \n",
+       "103           0.940309    0.977069    0.021970    0.911637    0.028395   \n",
+       "\n",
+       "Unnamed: 0  cg25458538  cg09261072  cg02404579  cg04118974  cg01236347  ...  \\\n",
+       "147           0.874494    0.580354    0.848220    0.732272    0.729814  ...   \n",
+       "123           0.898642    0.672970    0.872005    0.709339    0.703964  ...   \n",
+       "111           0.911834    0.586978    0.874440    0.747679    0.725431  ...   \n",
+       "81            0.860132    0.559542    0.810488    0.662618    0.601927  ...   \n",
+       "19            0.889454    0.614411    0.840286    0.732261    0.719624  ...   \n",
+       "..                 ...         ...         ...         ...         ...  ...   \n",
+       "41            0.907213    0.648510    0.864150    0.632262    0.634195  ...   \n",
+       "121           0.907656    0.590956    0.853172    0.770850    0.777764  ...   \n",
+       "143           0.874872    0.606528    0.837673    0.721731    0.651609  ...   \n",
+       "29            0.901456    0.653031    0.882988    0.744746    0.733421  ...   \n",
+       "103           0.873748    0.547899    0.819265    0.689862    0.643268  ...   \n",
+       "\n",
+       "Unnamed: 0  cg23020486  cg10295858  cg11606463  cg04767756  cg05166473  \\\n",
+       "147           0.010867    0.934795    0.964980    0.977291    0.877755   \n",
+       "123           0.006162    0.955088    0.967771    0.973018    0.871426   \n",
+       "111           0.003528    0.950890    0.956282    0.962483    0.838458   \n",
+       "81            0.011977    0.951810    0.956689    0.968849    0.752360   \n",
+       "19            0.011912    0.951209    0.961675    0.973922    0.830171   \n",
+       "..                 ...         ...         ...         ...         ...   \n",
+       "41            0.047900    0.951220    0.961997    0.961776    0.799364   \n",
+       "121           0.056822    0.944244    0.955128    0.966364    0.866610   \n",
+       "143           0.009074    0.951921    0.965835    0.968034    0.824260   \n",
+       "29            0.002640    0.963313    0.968439    0.969757    0.876919   \n",
+       "103           0.005453    0.952067    0.964782    0.968374    0.801423   \n",
+       "\n",
+       "Unnamed: 0  cg19812938  cg06272054  cg07255356  cg24220897  cg12325588  \n",
+       "147           0.909622    0.007554    0.015903    0.962175    0.012816  \n",
+       "123           0.910810    0.001273    0.004006    0.964292    0.004801  \n",
+       "111           0.919360    0.010293    0.013462    0.967021    0.019233  \n",
+       "81            0.888231    0.014288    0.016157    0.963459    0.001869  \n",
+       "19            0.909684    0.004134    0.008814    0.962250    0.009267  \n",
+       "..                 ...         ...         ...         ...         ...  \n",
+       "41            0.911416    0.011963    0.013717    0.944111    0.013061  \n",
+       "121           0.893951    0.011442    0.015364    0.938603    0.012846  \n",
+       "143           0.893882    0.015032    0.008654    0.967088    0.009491  \n",
+       "29            0.903055    0.008123    0.009624    0.977987    0.002156  \n",
+       "103           0.901259    0.010529    0.002935    0.911680    0.015609  \n",
+       "\n",
+       "[64 rows x 722696 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X = X_train \n",
+    "y = y_train\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
+    "def class_distribution(y):\n",
+    "    counts = np.bincount(y)\n",
+    "    labels = np.arange(len(counts))\n",
+    "    return pd.DataFrame({\n",
+    "        'Class': labels,\n",
+    "        'Count': counts,\n",
+    "        'Percentage': counts / len(y) * 100\n",
+    "    })\n",
+    "\n",
+    "# 訓練集類別分佈\n",
+    "train_dist = class_distribution(y_train)\n",
+    "print(\"訓練集類別分佈:\")\n",
+    "print(train_dist)\n",
+    "\n",
+    "# 測試集類別分佈\n",
+    "test_dist = class_distribution(y_test)\n",
+    "print(\"\\n測試集類別分佈:\")\n",
+    "print(test_dist)\n",
+    "\n",
+    "# 也可以顯示總數量\n",
+    "print(\"\\n訓練集和測試集的大小:\")\n",
+    "print(f\"訓練集大小: {len(X_train)}\")\n",
+    "print(f\"測試集大小: {len(X_test)}\")\n",
+    "X_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gene</th>\n",
+       "      <th>dbeta</th>\n",
+       "      <th>feature</th>\n",
+       "      <th>ID</th>\n",
+       "      <th>cluster</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>CMTM5</td>\n",
+       "      <td>0.172075</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>CX3CL1</td>\n",
+       "      <td>0.198136</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>CYP1A1</td>\n",
+       "      <td>0.195047</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg00213123</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>MIR1180</td>\n",
+       "      <td>0.157648</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg19157647</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>MIR124-3</td>\n",
+       "      <td>0.177844</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>NEFM</td>\n",
+       "      <td>0.227250</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg07552803</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>PCYT2</td>\n",
+       "      <td>0.154787</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg20248866</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>PTF1A</td>\n",
+       "      <td>0.189984</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg22746058</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>SALL3</td>\n",
+       "      <td>0.151857</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg05884032</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>SOX1</td>\n",
+       "      <td>0.228038</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg02547394</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>SPAG6</td>\n",
+       "      <td>0.281363</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg12610471</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>TP73</td>\n",
+       "      <td>0.209996</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg24073122</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        gene     dbeta  feature          ID  cluster\n",
+       "2      CMTM5  0.172075   TSS200  cg23631930        2\n",
+       "3     CX3CL1  0.198136  TSS1500  cg05724197        2\n",
+       "5     CYP1A1  0.195047  TSS1500  cg00213123        4\n",
+       "15   MIR1180  0.157648   TSS200  cg19157647        1\n",
+       "16  MIR124-3  0.177844  TSS1500  cg04927004        1\n",
+       "20      NEFM  0.227250  TSS1500  cg07552803        3\n",
+       "21     PCYT2  0.154787  TSS1500  cg20248866        4\n",
+       "23     PTF1A  0.189984  TSS1500  cg22746058        4\n",
+       "25     SALL3  0.151857   TSS200  cg05884032        4\n",
+       "28      SOX1  0.228038   TSS200  cg02547394        4\n",
+       "29     SPAG6  0.281363   TSS200  cg12610471        2\n",
+       "32      TP73  0.209996  TSS1500  cg24073122        4"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "input_path = (\n",
+    "    \"result/final_xzh/boruta_consensus_clustering_result_xzh_correct_cluster.csv\"  # example\n",
+    ")\n",
+    "final_gene = pd.read_csv(input_path)\n",
+    "# final_gene = pd.merge(final_gene, dbeta, on=\"gene\", how=\"inner\")\n",
+    "final_gene = final_gene[final_gene['dbeta'] > 0]\n",
+    "final_gene\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[['cg19157647', 'cg23631930', 'cg07552803', 'cg00213123'],\n",
+       " ['cg19157647', 'cg23631930', 'cg07552803', 'cg20248866'],\n",
+       " ['cg19157647', 'cg23631930', 'cg07552803', 'cg22746058'],\n",
+       " ['cg19157647', 'cg23631930', 'cg07552803', 'cg05884032'],\n",
+       " ['cg19157647', 'cg23631930', 'cg07552803', 'cg02547394'],\n",
+       " ['cg19157647', 'cg23631930', 'cg07552803', 'cg24073122'],\n",
+       " ['cg19157647', 'cg05724197', 'cg07552803', 'cg00213123'],\n",
+       " ['cg19157647', 'cg05724197', 'cg07552803', 'cg20248866'],\n",
+       " ['cg19157647', 'cg05724197', 'cg07552803', 'cg22746058'],\n",
+       " ['cg19157647', 'cg05724197', 'cg07552803', 'cg05884032'],\n",
+       " ['cg19157647', 'cg05724197', 'cg07552803', 'cg02547394'],\n",
+       " ['cg19157647', 'cg05724197', 'cg07552803', 'cg24073122'],\n",
+       " ['cg19157647', 'cg12610471', 'cg07552803', 'cg00213123'],\n",
+       " ['cg19157647', 'cg12610471', 'cg07552803', 'cg20248866'],\n",
+       " ['cg19157647', 'cg12610471', 'cg07552803', 'cg22746058'],\n",
+       " ['cg19157647', 'cg12610471', 'cg07552803', 'cg05884032'],\n",
+       " ['cg19157647', 'cg12610471', 'cg07552803', 'cg02547394'],\n",
+       " ['cg19157647', 'cg12610471', 'cg07552803', 'cg24073122'],\n",
+       " ['cg04927004', 'cg23631930', 'cg07552803', 'cg00213123'],\n",
+       " ['cg04927004', 'cg23631930', 'cg07552803', 'cg20248866'],\n",
+       " ['cg04927004', 'cg23631930', 'cg07552803', 'cg22746058'],\n",
+       " ['cg04927004', 'cg23631930', 'cg07552803', 'cg05884032'],\n",
+       " ['cg04927004', 'cg23631930', 'cg07552803', 'cg02547394'],\n",
+       " ['cg04927004', 'cg23631930', 'cg07552803', 'cg24073122'],\n",
+       " ['cg04927004', 'cg05724197', 'cg07552803', 'cg00213123'],\n",
+       " ['cg04927004', 'cg05724197', 'cg07552803', 'cg20248866'],\n",
+       " ['cg04927004', 'cg05724197', 'cg07552803', 'cg22746058'],\n",
+       " ['cg04927004', 'cg05724197', 'cg07552803', 'cg05884032'],\n",
+       " ['cg04927004', 'cg05724197', 'cg07552803', 'cg02547394'],\n",
+       " ['cg04927004', 'cg05724197', 'cg07552803', 'cg24073122'],\n",
+       " ['cg04927004', 'cg12610471', 'cg07552803', 'cg00213123'],\n",
+       " ['cg04927004', 'cg12610471', 'cg07552803', 'cg20248866'],\n",
+       " ['cg04927004', 'cg12610471', 'cg07552803', 'cg22746058'],\n",
+       " ['cg04927004', 'cg12610471', 'cg07552803', 'cg05884032'],\n",
+       " ['cg04927004', 'cg12610471', 'cg07552803', 'cg02547394'],\n",
+       " ['cg04927004', 'cg12610471', 'cg07552803', 'cg24073122']]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# 須包含ID和cluster欄位\n",
+    "\n",
+    "# 根據 Cluster 分組\n",
+    "import pandas as pd\n",
+    "import itertools\n",
+    "grouped = final_gene.groupby('cluster')\n",
+    "\n",
+    "# 生成排列組合\n",
+    "combinations = list(itertools.product(*[group.values.tolist() for _, group in grouped]))\n",
+    "# print(combinations)\n",
+    "# 將結果轉換為所需格式\n",
+    "result = []\n",
+    "for combo in combinations:\n",
+    "    result.append([row[3] for row in combo])  # row[0] 對應的是 Gene 列\n",
+    "\n",
+    "cg_list = result\n",
+    "cg_list"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "from sklearn.svm import SVC\n",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "import xgboost as xgb\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.metrics import classification_report, roc_auc_score, accuracy_score, precision_score, recall_score, f1_score\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from xgboost import XGBClassifier\n",
+    "from sklearn.model_selection import RandomizedSearchCV\n",
+    "from sklearn.model_selection import GridSearchCV\n",
+    "from skopt import BayesSearchCV\n",
+    "from skopt.space import Categorical, Real\n",
+    "from sklearn.metrics import (\n",
+    "    confusion_matrix,\n",
+    "    precision_score,\n",
+    "    accuracy_score,\n",
+    "    matthews_corrcoef,\n",
+    "    f1_score,\n",
+    ")\n",
+    "\n",
+    "\n",
+    "tree_params = {\"max_depth\": [3, 5, 7], \"min_samples_split\": [2, 5, 10]}\n",
+    "\n",
+    "clf_tree = DecisionTreeClassifier()\n",
+    "\n",
+    "lr_params = [\n",
+    "   {\"C\": [0.001,0.01,0.1, 1, 10], \"solver\": [\"liblinear\"]}\n",
+    "]\n",
+    "\n",
+    "clf_lr = LogisticRegression(max_iter=500) \n",
+    "\n",
+    "\n",
+    "rf_params = {\n",
+    "        \"n_estimators\": [100,150, 200],\n",
+    "        \"max_depth\": [1,3, 5, 7],\n",
+    "        \"min_samples_split\": [2, 5, 10],\n",
+    "    }\n",
+    "clf_rf = RandomForestClassifier()\n",
+    "\n",
+    "svm_params = {\"C\": [0.001,0.1, 1, 10,100,1000], \"kernel\": [\"linear\", \"rbf\"]}\n",
+    "\n",
+    "clf_svm = SVC(probability=True)\n",
+    "\n",
+    "\n",
+    "xgb_params = {\n",
+    "        \"n_estimators\": [100,150, 200],\n",
+    "        \"max_depth\": [3, 5, 7],\n",
+    "        \"learning_rate\": [0.01, 0.1, 0.2],\n",
+    "    }\n",
+    "\n",
+    "clf_xgb = XGBClassifier( eval_metric='logloss')\n",
+    "\n",
+    "results = []\n",
+    "\n",
+    "model_list = [clf_tree,clf_lr,clf_rf,clf_svm,clf_xgb]\n",
+    "model_param = [tree_params,lr_params,rf_params,svm_params,xgb_params]\n",
+    "model_names = ['Decision Tree', 'Logistic Regression', 'Random Forest', 'SVM', 'XGBoost']\n",
+    "\n",
+    "for cg in cg_list:\n",
+    "    X_train_c = X_train[cg]\n",
+    "    X_test_c = X_test[cg]\n",
+    "    \n",
+    "    for model,param, model_name in zip(model_list,model_param, model_names):\n",
+    "        \n",
+    "        model = GridSearchCV(\n",
+    "                    estimator=model, param_grid=param, cv=5, n_jobs=-1\n",
+    "        )\n",
+    "        model.fit(X_train_c, y_train)\n",
+    "        \n",
+    "        y_pred = model.predict(X_test_c)\n",
+    "        y_pred_prob = model.predict_proba(X_test_c)[:, 1]\n",
+    "        \n",
+    "        y_pred_train = model.predict(X_train_c)\n",
+    "        y_pred_prob_train = model.predict_proba(X_train_c)[:, 1]\n",
+    "        # report = classification_report(y_test, y_pred, output_dict=True)\n",
+    "        auc = roc_auc_score(y_test, y_pred_prob)\n",
+    "        \n",
+    "        train_accuracy = accuracy_score(y_train, y_pred_train)\n",
+    "        test_accuracy = accuracy_score(y_test, y_pred)\n",
+    "        precision = precision_score(y_test, y_pred)\n",
+    "        sensitivity = recall_score(y_test, y_pred)\n",
+    "        specificity = recall_score(y_test, y_pred, pos_label=0)\n",
+    "        f1 = f1_score(y_test, y_pred)\n",
+    "        mcc = matthews_corrcoef(y_test, y_pred)\n",
+    "\n",
+    "        # 計算複合指標\\\n",
+    "        \n",
+    "        results.append( {\n",
+    "            'Model': model_name,\n",
+    "            'ID1': cg[0],\n",
+    "            'ID2': cg[1],\n",
+    "            'ID3': cg[2],\n",
+    "            'ID4': cg[3],\n",
+    "            'train_accuracy': train_accuracy,\n",
+    "            'test_accuracy': test_accuracy,\n",
+    "            'train - test accuracy' : train_accuracy - test_accuracy,\n",
+    "            'AUC': auc,\n",
+    "            'f1-score': f1,\n",
+    "            'sensitivity': sensitivity,\n",
+    "            'specificity': specificity,\n",
+    "            'precision': precision,\n",
+    "            'mcc' : mcc\n",
+    "        })\n",
+    "df = pd.DataFrame(results)\n",
+    "\n",
+    "df\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "df.to_csv(\"result/test_aba2/5_fold_850k_hyper.csv\",index=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 89093"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "beta_normalized_89093 = \"source/GSE89093/GSE89093.csv\"\n",
+    "label_89093 = \"source/GSE89093/phenotype.csv\"\n",
+    "\n",
+    "data_89093 = pd.read_csv(beta_normalized_89093)\n",
+    "data_89093_label = pd.read_csv(label_89093)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>82</th>\n",
+       "      <th>83</th>\n",
+       "      <th>84</th>\n",
+       "      <th>85</th>\n",
+       "      <th>86</th>\n",
+       "      <th>87</th>\n",
+       "      <th>88</th>\n",
+       "      <th>89</th>\n",
+       "      <th>90</th>\n",
+       "      <th>91</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ID_REF</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>cg00213123</th>\n",
+       "      <td>0.192641</td>\n",
+       "      <td>0.226033</td>\n",
+       "      <td>0.192003</td>\n",
+       "      <td>0.150712</td>\n",
+       "      <td>0.235921</td>\n",
+       "      <td>0.257851</td>\n",
+       "      <td>0.260224</td>\n",
+       "      <td>0.247907</td>\n",
+       "      <td>0.221343</td>\n",
+       "      <td>0.139146</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.229828</td>\n",
+       "      <td>0.204323</td>\n",
+       "      <td>0.178284</td>\n",
+       "      <td>0.201562</td>\n",
+       "      <td>0.221746</td>\n",
+       "      <td>0.273957</td>\n",
+       "      <td>0.204695</td>\n",
+       "      <td>0.236391</td>\n",
+       "      <td>0.246210</td>\n",
+       "      <td>0.220037</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg02547394</th>\n",
+       "      <td>0.209522</td>\n",
+       "      <td>0.218504</td>\n",
+       "      <td>0.156773</td>\n",
+       "      <td>0.135419</td>\n",
+       "      <td>0.218601</td>\n",
+       "      <td>0.144728</td>\n",
+       "      <td>0.190189</td>\n",
+       "      <td>0.189959</td>\n",
+       "      <td>0.151522</td>\n",
+       "      <td>0.095937</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.168689</td>\n",
+       "      <td>0.177006</td>\n",
+       "      <td>0.140306</td>\n",
+       "      <td>0.152126</td>\n",
+       "      <td>0.139817</td>\n",
+       "      <td>0.435037</td>\n",
+       "      <td>0.182890</td>\n",
+       "      <td>0.149019</td>\n",
+       "      <td>0.163937</td>\n",
+       "      <td>0.177328</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg04927004</th>\n",
+       "      <td>0.183700</td>\n",
+       "      <td>0.271888</td>\n",
+       "      <td>0.253845</td>\n",
+       "      <td>0.329069</td>\n",
+       "      <td>0.276557</td>\n",
+       "      <td>0.263308</td>\n",
+       "      <td>0.237192</td>\n",
+       "      <td>0.308882</td>\n",
+       "      <td>0.267855</td>\n",
+       "      <td>0.184488</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.243953</td>\n",
+       "      <td>0.231732</td>\n",
+       "      <td>0.234402</td>\n",
+       "      <td>0.218756</td>\n",
+       "      <td>0.244129</td>\n",
+       "      <td>0.262375</td>\n",
+       "      <td>0.231248</td>\n",
+       "      <td>0.248455</td>\n",
+       "      <td>0.255094</td>\n",
+       "      <td>0.250802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg05724197</th>\n",
+       "      <td>0.881470</td>\n",
+       "      <td>0.781956</td>\n",
+       "      <td>0.791505</td>\n",
+       "      <td>0.827658</td>\n",
+       "      <td>0.827168</td>\n",
+       "      <td>0.816100</td>\n",
+       "      <td>0.797156</td>\n",
+       "      <td>0.817910</td>\n",
+       "      <td>0.867192</td>\n",
+       "      <td>0.862168</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.793264</td>\n",
+       "      <td>0.893796</td>\n",
+       "      <td>0.859082</td>\n",
+       "      <td>0.858964</td>\n",
+       "      <td>0.786986</td>\n",
+       "      <td>0.787780</td>\n",
+       "      <td>0.828101</td>\n",
+       "      <td>0.771231</td>\n",
+       "      <td>0.747346</td>\n",
+       "      <td>0.826932</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg05884032</th>\n",
+       "      <td>0.035773</td>\n",
+       "      <td>0.128722</td>\n",
+       "      <td>0.183718</td>\n",
+       "      <td>0.117518</td>\n",
+       "      <td>0.129957</td>\n",
+       "      <td>0.084905</td>\n",
+       "      <td>0.097592</td>\n",
+       "      <td>0.100434</td>\n",
+       "      <td>0.057997</td>\n",
+       "      <td>0.080908</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.123427</td>\n",
+       "      <td>0.079221</td>\n",
+       "      <td>0.053397</td>\n",
+       "      <td>0.055639</td>\n",
+       "      <td>0.078975</td>\n",
+       "      <td>0.116359</td>\n",
+       "      <td>0.081860</td>\n",
+       "      <td>0.119291</td>\n",
+       "      <td>0.111124</td>\n",
+       "      <td>0.128325</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg07552803</th>\n",
+       "      <td>0.111795</td>\n",
+       "      <td>0.139862</td>\n",
+       "      <td>0.129328</td>\n",
+       "      <td>0.116214</td>\n",
+       "      <td>0.150056</td>\n",
+       "      <td>0.117123</td>\n",
+       "      <td>0.155182</td>\n",
+       "      <td>0.129048</td>\n",
+       "      <td>0.118683</td>\n",
+       "      <td>0.084462</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.164191</td>\n",
+       "      <td>0.158666</td>\n",
+       "      <td>0.114439</td>\n",
+       "      <td>0.108614</td>\n",
+       "      <td>0.125877</td>\n",
+       "      <td>0.211528</td>\n",
+       "      <td>0.128582</td>\n",
+       "      <td>0.101510</td>\n",
+       "      <td>0.151759</td>\n",
+       "      <td>0.142964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg12610471</th>\n",
+       "      <td>0.190469</td>\n",
+       "      <td>0.211051</td>\n",
+       "      <td>0.193113</td>\n",
+       "      <td>0.222155</td>\n",
+       "      <td>0.195286</td>\n",
+       "      <td>0.178723</td>\n",
+       "      <td>0.222941</td>\n",
+       "      <td>0.215148</td>\n",
+       "      <td>0.149299</td>\n",
+       "      <td>0.124172</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.164175</td>\n",
+       "      <td>0.182578</td>\n",
+       "      <td>0.138807</td>\n",
+       "      <td>0.176600</td>\n",
+       "      <td>0.167714</td>\n",
+       "      <td>0.216716</td>\n",
+       "      <td>0.183422</td>\n",
+       "      <td>0.190460</td>\n",
+       "      <td>0.177718</td>\n",
+       "      <td>0.143805</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg19157647</th>\n",
+       "      <td>0.936529</td>\n",
+       "      <td>0.918074</td>\n",
+       "      <td>0.932604</td>\n",
+       "      <td>0.944588</td>\n",
+       "      <td>0.953895</td>\n",
+       "      <td>0.951862</td>\n",
+       "      <td>0.926035</td>\n",
+       "      <td>0.927300</td>\n",
+       "      <td>0.977846</td>\n",
+       "      <td>0.975092</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.936031</td>\n",
+       "      <td>0.954918</td>\n",
+       "      <td>0.944655</td>\n",
+       "      <td>0.949902</td>\n",
+       "      <td>0.924236</td>\n",
+       "      <td>0.913046</td>\n",
+       "      <td>0.929575</td>\n",
+       "      <td>0.930065</td>\n",
+       "      <td>0.914998</td>\n",
+       "      <td>0.934900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg20248866</th>\n",
+       "      <td>0.387897</td>\n",
+       "      <td>0.465436</td>\n",
+       "      <td>0.497281</td>\n",
+       "      <td>0.458328</td>\n",
+       "      <td>0.419680</td>\n",
+       "      <td>0.502283</td>\n",
+       "      <td>0.492227</td>\n",
+       "      <td>0.490115</td>\n",
+       "      <td>0.440984</td>\n",
+       "      <td>0.436178</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.552442</td>\n",
+       "      <td>0.492607</td>\n",
+       "      <td>0.376805</td>\n",
+       "      <td>0.423728</td>\n",
+       "      <td>0.468667</td>\n",
+       "      <td>0.541542</td>\n",
+       "      <td>0.395736</td>\n",
+       "      <td>0.460566</td>\n",
+       "      <td>0.507808</td>\n",
+       "      <td>0.571862</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg22746058</th>\n",
+       "      <td>0.097518</td>\n",
+       "      <td>0.147684</td>\n",
+       "      <td>0.128428</td>\n",
+       "      <td>0.119829</td>\n",
+       "      <td>0.164012</td>\n",
+       "      <td>0.132210</td>\n",
+       "      <td>0.122086</td>\n",
+       "      <td>0.141626</td>\n",
+       "      <td>0.139138</td>\n",
+       "      <td>0.098904</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.116953</td>\n",
+       "      <td>0.131821</td>\n",
+       "      <td>0.122928</td>\n",
+       "      <td>0.114842</td>\n",
+       "      <td>0.157544</td>\n",
+       "      <td>0.196218</td>\n",
+       "      <td>0.153728</td>\n",
+       "      <td>0.138676</td>\n",
+       "      <td>0.182450</td>\n",
+       "      <td>0.123431</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg23631930</th>\n",
+       "      <td>0.842356</td>\n",
+       "      <td>0.833117</td>\n",
+       "      <td>0.848755</td>\n",
+       "      <td>0.881845</td>\n",
+       "      <td>0.937611</td>\n",
+       "      <td>0.890335</td>\n",
+       "      <td>0.863096</td>\n",
+       "      <td>0.835016</td>\n",
+       "      <td>0.934152</td>\n",
+       "      <td>0.940110</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.854575</td>\n",
+       "      <td>0.837046</td>\n",
+       "      <td>0.838897</td>\n",
+       "      <td>0.878913</td>\n",
+       "      <td>0.840206</td>\n",
+       "      <td>0.800660</td>\n",
+       "      <td>0.812603</td>\n",
+       "      <td>0.813023</td>\n",
+       "      <td>0.820174</td>\n",
+       "      <td>0.859444</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg24073122</th>\n",
+       "      <td>0.074294</td>\n",
+       "      <td>0.151638</td>\n",
+       "      <td>0.142362</td>\n",
+       "      <td>0.094227</td>\n",
+       "      <td>0.110080</td>\n",
+       "      <td>0.105853</td>\n",
+       "      <td>0.142996</td>\n",
+       "      <td>0.142974</td>\n",
+       "      <td>0.084721</td>\n",
+       "      <td>0.049366</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.123441</td>\n",
+       "      <td>0.123334</td>\n",
+       "      <td>0.109523</td>\n",
+       "      <td>0.124184</td>\n",
+       "      <td>0.101531</td>\n",
+       "      <td>0.209295</td>\n",
+       "      <td>0.123979</td>\n",
+       "      <td>0.133271</td>\n",
+       "      <td>0.142449</td>\n",
+       "      <td>0.119534</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>12 rows × 92 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   0         1         2         3         4         5  \\\n",
+       "ID_REF                                                                   \n",
+       "cg00213123  0.192641  0.226033  0.192003  0.150712  0.235921  0.257851   \n",
+       "cg02547394  0.209522  0.218504  0.156773  0.135419  0.218601  0.144728   \n",
+       "cg04927004  0.183700  0.271888  0.253845  0.329069  0.276557  0.263308   \n",
+       "cg05724197  0.881470  0.781956  0.791505  0.827658  0.827168  0.816100   \n",
+       "cg05884032  0.035773  0.128722  0.183718  0.117518  0.129957  0.084905   \n",
+       "cg07552803  0.111795  0.139862  0.129328  0.116214  0.150056  0.117123   \n",
+       "cg12610471  0.190469  0.211051  0.193113  0.222155  0.195286  0.178723   \n",
+       "cg19157647  0.936529  0.918074  0.932604  0.944588  0.953895  0.951862   \n",
+       "cg20248866  0.387897  0.465436  0.497281  0.458328  0.419680  0.502283   \n",
+       "cg22746058  0.097518  0.147684  0.128428  0.119829  0.164012  0.132210   \n",
+       "cg23631930  0.842356  0.833117  0.848755  0.881845  0.937611  0.890335   \n",
+       "cg24073122  0.074294  0.151638  0.142362  0.094227  0.110080  0.105853   \n",
+       "\n",
+       "                   6         7         8         9  ...        82        83  \\\n",
+       "ID_REF                                              ...                       \n",
+       "cg00213123  0.260224  0.247907  0.221343  0.139146  ...  0.229828  0.204323   \n",
+       "cg02547394  0.190189  0.189959  0.151522  0.095937  ...  0.168689  0.177006   \n",
+       "cg04927004  0.237192  0.308882  0.267855  0.184488  ...  0.243953  0.231732   \n",
+       "cg05724197  0.797156  0.817910  0.867192  0.862168  ...  0.793264  0.893796   \n",
+       "cg05884032  0.097592  0.100434  0.057997  0.080908  ...  0.123427  0.079221   \n",
+       "cg07552803  0.155182  0.129048  0.118683  0.084462  ...  0.164191  0.158666   \n",
+       "cg12610471  0.222941  0.215148  0.149299  0.124172  ...  0.164175  0.182578   \n",
+       "cg19157647  0.926035  0.927300  0.977846  0.975092  ...  0.936031  0.954918   \n",
+       "cg20248866  0.492227  0.490115  0.440984  0.436178  ...  0.552442  0.492607   \n",
+       "cg22746058  0.122086  0.141626  0.139138  0.098904  ...  0.116953  0.131821   \n",
+       "cg23631930  0.863096  0.835016  0.934152  0.940110  ...  0.854575  0.837046   \n",
+       "cg24073122  0.142996  0.142974  0.084721  0.049366  ...  0.123441  0.123334   \n",
+       "\n",
+       "                  84        85        86        87        88        89  \\\n",
+       "ID_REF                                                                   \n",
+       "cg00213123  0.178284  0.201562  0.221746  0.273957  0.204695  0.236391   \n",
+       "cg02547394  0.140306  0.152126  0.139817  0.435037  0.182890  0.149019   \n",
+       "cg04927004  0.234402  0.218756  0.244129  0.262375  0.231248  0.248455   \n",
+       "cg05724197  0.859082  0.858964  0.786986  0.787780  0.828101  0.771231   \n",
+       "cg05884032  0.053397  0.055639  0.078975  0.116359  0.081860  0.119291   \n",
+       "cg07552803  0.114439  0.108614  0.125877  0.211528  0.128582  0.101510   \n",
+       "cg12610471  0.138807  0.176600  0.167714  0.216716  0.183422  0.190460   \n",
+       "cg19157647  0.944655  0.949902  0.924236  0.913046  0.929575  0.930065   \n",
+       "cg20248866  0.376805  0.423728  0.468667  0.541542  0.395736  0.460566   \n",
+       "cg22746058  0.122928  0.114842  0.157544  0.196218  0.153728  0.138676   \n",
+       "cg23631930  0.838897  0.878913  0.840206  0.800660  0.812603  0.813023   \n",
+       "cg24073122  0.109523  0.124184  0.101531  0.209295  0.123979  0.133271   \n",
+       "\n",
+       "                  90        91  \n",
+       "ID_REF                          \n",
+       "cg00213123  0.246210  0.220037  \n",
+       "cg02547394  0.163937  0.177328  \n",
+       "cg04927004  0.255094  0.250802  \n",
+       "cg05724197  0.747346  0.826932  \n",
+       "cg05884032  0.111124  0.128325  \n",
+       "cg07552803  0.151759  0.142964  \n",
+       "cg12610471  0.177718  0.143805  \n",
+       "cg19157647  0.914998  0.934900  \n",
+       "cg20248866  0.507808  0.571862  \n",
+       "cg22746058  0.182450  0.123431  \n",
+       "cg23631930  0.820174  0.859444  \n",
+       "cg24073122  0.142449  0.119534  \n",
+       "\n",
+       "[12 rows x 92 columns]"
+      ]
+     },
+     "execution_count": 93,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_89093_label = pd.DataFrame(data_89093_label[\"cancer_status\"])\n",
+    "\n",
+    "# 檢查挑選出的特徵是否都有出現\n",
+    "data_89093 = data_89093[data_89093[\"ID_REF\"].isin(final_gene[\"ID\"])]\n",
+    "data_89093.set_index(\"ID_REF\", inplace=True)\n",
+    "data_89093"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y_test_89093 = [\n",
+    "    0 if data_89093_label.iloc[i, 0] == \"healthy\" else 1\n",
+    "    for i in range(data_89093_label.shape[0])\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(92, 12) 92\n",
+      "訓練集類別分佈:\n",
+      "   Class  Count  Percentage\n",
+      "0      0     36   49.315068\n",
+      "1      1     37   50.684932\n",
+      "\n",
+      "測試集類別分佈:\n",
+      "   Class  Count  Percentage\n",
+      "0      0     10   52.631579\n",
+      "1      1      9   47.368421\n",
+      "\n",
+      "訓練集和測試集的大小:\n",
+      "訓練集大小: 73\n",
+      "測試集大小: 19\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>ID_REF</th>\n",
+       "      <th>cg00213123</th>\n",
+       "      <th>cg02547394</th>\n",
+       "      <th>cg04927004</th>\n",
+       "      <th>cg05724197</th>\n",
+       "      <th>cg05884032</th>\n",
+       "      <th>cg07552803</th>\n",
+       "      <th>cg12610471</th>\n",
+       "      <th>cg19157647</th>\n",
+       "      <th>cg20248866</th>\n",
+       "      <th>cg22746058</th>\n",
+       "      <th>cg23631930</th>\n",
+       "      <th>cg24073122</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>65</th>\n",
+       "      <td>0.276734</td>\n",
+       "      <td>0.190227</td>\n",
+       "      <td>0.226529</td>\n",
+       "      <td>0.858188</td>\n",
+       "      <td>0.105276</td>\n",
+       "      <td>0.231019</td>\n",
+       "      <td>0.200420</td>\n",
+       "      <td>0.956841</td>\n",
+       "      <td>0.580620</td>\n",
+       "      <td>0.186008</td>\n",
+       "      <td>0.860197</td>\n",
+       "      <td>0.198897</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>0.253825</td>\n",
+       "      <td>0.241473</td>\n",
+       "      <td>0.208582</td>\n",
+       "      <td>0.838284</td>\n",
+       "      <td>0.112708</td>\n",
+       "      <td>0.170608</td>\n",
+       "      <td>0.164555</td>\n",
+       "      <td>0.967148</td>\n",
+       "      <td>0.526162</td>\n",
+       "      <td>0.158694</td>\n",
+       "      <td>0.871927</td>\n",
+       "      <td>0.134052</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>68</th>\n",
+       "      <td>0.295146</td>\n",
+       "      <td>0.296080</td>\n",
+       "      <td>0.277791</td>\n",
+       "      <td>0.772005</td>\n",
+       "      <td>0.103734</td>\n",
+       "      <td>0.205804</td>\n",
+       "      <td>0.215415</td>\n",
+       "      <td>0.931302</td>\n",
+       "      <td>0.508505</td>\n",
+       "      <td>0.241113</td>\n",
+       "      <td>0.780040</td>\n",
+       "      <td>0.190257</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>78</th>\n",
+       "      <td>0.282719</td>\n",
+       "      <td>0.254573</td>\n",
+       "      <td>0.260540</td>\n",
+       "      <td>0.769523</td>\n",
+       "      <td>0.089074</td>\n",
+       "      <td>0.173621</td>\n",
+       "      <td>0.170045</td>\n",
+       "      <td>0.935334</td>\n",
+       "      <td>0.458227</td>\n",
+       "      <td>0.191908</td>\n",
+       "      <td>0.786792</td>\n",
+       "      <td>0.174281</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>0.153180</td>\n",
+       "      <td>0.144124</td>\n",
+       "      <td>0.244648</td>\n",
+       "      <td>0.863334</td>\n",
+       "      <td>0.076647</td>\n",
+       "      <td>0.162444</td>\n",
+       "      <td>0.208547</td>\n",
+       "      <td>0.951325</td>\n",
+       "      <td>0.486025</td>\n",
+       "      <td>0.125914</td>\n",
+       "      <td>0.886876</td>\n",
+       "      <td>0.118644</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>0.228484</td>\n",
+       "      <td>0.171401</td>\n",
+       "      <td>0.243677</td>\n",
+       "      <td>0.890451</td>\n",
+       "      <td>0.059369</td>\n",
+       "      <td>0.128549</td>\n",
+       "      <td>0.158581</td>\n",
+       "      <td>0.925604</td>\n",
+       "      <td>0.440604</td>\n",
+       "      <td>0.118990</td>\n",
+       "      <td>0.852424</td>\n",
+       "      <td>0.124386</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60</th>\n",
+       "      <td>0.197295</td>\n",
+       "      <td>0.136145</td>\n",
+       "      <td>0.181729</td>\n",
+       "      <td>0.921877</td>\n",
+       "      <td>0.055918</td>\n",
+       "      <td>0.124748</td>\n",
+       "      <td>0.148935</td>\n",
+       "      <td>0.956117</td>\n",
+       "      <td>0.573682</td>\n",
+       "      <td>0.109547</td>\n",
+       "      <td>0.888113</td>\n",
+       "      <td>0.091460</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>71</th>\n",
+       "      <td>0.237512</td>\n",
+       "      <td>0.208786</td>\n",
+       "      <td>0.279751</td>\n",
+       "      <td>0.837631</td>\n",
+       "      <td>0.033114</td>\n",
+       "      <td>0.109243</td>\n",
+       "      <td>0.172991</td>\n",
+       "      <td>0.902272</td>\n",
+       "      <td>0.480480</td>\n",
+       "      <td>0.124730</td>\n",
+       "      <td>0.851096</td>\n",
+       "      <td>0.117423</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>0.173133</td>\n",
+       "      <td>0.129268</td>\n",
+       "      <td>0.246479</td>\n",
+       "      <td>0.844835</td>\n",
+       "      <td>0.080551</td>\n",
+       "      <td>0.088834</td>\n",
+       "      <td>0.164010</td>\n",
+       "      <td>0.976279</td>\n",
+       "      <td>0.413539</td>\n",
+       "      <td>0.110516</td>\n",
+       "      <td>0.933183</td>\n",
+       "      <td>0.076993</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>0.282360</td>\n",
+       "      <td>0.160041</td>\n",
+       "      <td>0.192485</td>\n",
+       "      <td>0.825712</td>\n",
+       "      <td>0.062558</td>\n",
+       "      <td>0.129228</td>\n",
+       "      <td>0.180136</td>\n",
+       "      <td>0.941580</td>\n",
+       "      <td>0.493213</td>\n",
+       "      <td>0.149672</td>\n",
+       "      <td>0.880877</td>\n",
+       "      <td>0.124818</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>73 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "ID_REF  cg00213123  cg02547394  cg04927004  cg05724197  cg05884032  \\\n",
+       "65        0.276734    0.190227    0.226529    0.858188    0.105276   \n",
+       "15        0.253825    0.241473    0.208582    0.838284    0.112708   \n",
+       "68        0.295146    0.296080    0.277791    0.772005    0.103734   \n",
+       "78        0.282719    0.254573    0.260540    0.769523    0.089074   \n",
+       "30        0.153180    0.144124    0.244648    0.863334    0.076647   \n",
+       "..             ...         ...         ...         ...         ...   \n",
+       "20        0.228484    0.171401    0.243677    0.890451    0.059369   \n",
+       "60        0.197295    0.136145    0.181729    0.921877    0.055918   \n",
+       "71        0.237512    0.208786    0.279751    0.837631    0.033114   \n",
+       "14        0.173133    0.129268    0.246479    0.844835    0.080551   \n",
+       "51        0.282360    0.160041    0.192485    0.825712    0.062558   \n",
+       "\n",
+       "ID_REF  cg07552803  cg12610471  cg19157647  cg20248866  cg22746058  \\\n",
+       "65        0.231019    0.200420    0.956841    0.580620    0.186008   \n",
+       "15        0.170608    0.164555    0.967148    0.526162    0.158694   \n",
+       "68        0.205804    0.215415    0.931302    0.508505    0.241113   \n",
+       "78        0.173621    0.170045    0.935334    0.458227    0.191908   \n",
+       "30        0.162444    0.208547    0.951325    0.486025    0.125914   \n",
+       "..             ...         ...         ...         ...         ...   \n",
+       "20        0.128549    0.158581    0.925604    0.440604    0.118990   \n",
+       "60        0.124748    0.148935    0.956117    0.573682    0.109547   \n",
+       "71        0.109243    0.172991    0.902272    0.480480    0.124730   \n",
+       "14        0.088834    0.164010    0.976279    0.413539    0.110516   \n",
+       "51        0.129228    0.180136    0.941580    0.493213    0.149672   \n",
+       "\n",
+       "ID_REF  cg23631930  cg24073122  \n",
+       "65        0.860197    0.198897  \n",
+       "15        0.871927    0.134052  \n",
+       "68        0.780040    0.190257  \n",
+       "78        0.786792    0.174281  \n",
+       "30        0.886876    0.118644  \n",
+       "..             ...         ...  \n",
+       "20        0.852424    0.124386  \n",
+       "60        0.888113    0.091460  \n",
+       "71        0.851096    0.117423  \n",
+       "14        0.933183    0.076993  \n",
+       "51        0.880877    0.124818  \n",
+       "\n",
+       "[73 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 95,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X = data_89093.T \n",
+    "y = y_test_89093\n",
+    "print(X.shape,len(y))\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
+    "def class_distribution(y):\n",
+    "    counts = np.bincount(y)\n",
+    "    labels = np.arange(len(counts))\n",
+    "    return pd.DataFrame({\n",
+    "        'Class': labels,\n",
+    "        'Count': counts,\n",
+    "        'Percentage': counts / len(y) * 100\n",
+    "    })\n",
+    "\n",
+    "# 訓練集類別分佈\n",
+    "train_dist = class_distribution(y_train)\n",
+    "print(\"訓練集類別分佈:\")\n",
+    "print(train_dist)\n",
+    "\n",
+    "# 測試集類別分佈\n",
+    "test_dist = class_distribution(y_test)\n",
+    "print(\"\\n測試集類別分佈:\")\n",
+    "print(test_dist)\n",
+    "\n",
+    "# 也可以顯示總數量\n",
+    "print(\"\\n訓練集和測試集的大小:\")\n",
+    "print(f\"訓練集大小: {len(X_train)}\")\n",
+    "print(f\"測試集大小: {len(X_test)}\")\n",
+    "X_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gene</th>\n",
+       "      <th>cluster</th>\n",
+       "      <th>ID</th>\n",
+       "      <th>dbeta</th>\n",
+       "      <th>feature_x</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>CMTM5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>0.172075</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>CX3CL1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>0.198136</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>CYP1A1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>cg00213123</td>\n",
+       "      <td>0.195047</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>MIR1180</td>\n",
+       "      <td>1</td>\n",
+       "      <td>cg19157647</td>\n",
+       "      <td>0.157648</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>MIR124-3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>0.177844</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>NEFM</td>\n",
+       "      <td>4</td>\n",
+       "      <td>cg07552803</td>\n",
+       "      <td>0.227250</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>PCYT2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>cg20248866</td>\n",
+       "      <td>0.154787</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>PTF1A</td>\n",
+       "      <td>3</td>\n",
+       "      <td>cg22746058</td>\n",
+       "      <td>0.189984</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>SALL3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>cg05884032</td>\n",
+       "      <td>0.151857</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>SOX1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>cg02547394</td>\n",
+       "      <td>0.228038</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>SPAG6</td>\n",
+       "      <td>4</td>\n",
+       "      <td>cg12610471</td>\n",
+       "      <td>0.281363</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>TP73</td>\n",
+       "      <td>3</td>\n",
+       "      <td>cg24073122</td>\n",
+       "      <td>0.209996</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        gene  cluster          ID     dbeta feature_x\n",
+       "2      CMTM5        2  cg23631930  0.172075    TSS200\n",
+       "3     CX3CL1        2  cg05724197  0.198136   TSS1500\n",
+       "5     CYP1A1        4  cg00213123  0.195047   TSS1500\n",
+       "15   MIR1180        1  cg19157647  0.157648    TSS200\n",
+       "16  MIR124-3        1  cg04927004  0.177844   TSS1500\n",
+       "20      NEFM        4  cg07552803  0.227250   TSS1500\n",
+       "21     PCYT2        4  cg20248866  0.154787   TSS1500\n",
+       "23     PTF1A        3  cg22746058  0.189984   TSS1500\n",
+       "25     SALL3        3  cg05884032  0.151857    TSS200\n",
+       "28      SOX1        3  cg02547394  0.228038    TSS200\n",
+       "29     SPAG6        4  cg12610471  0.281363    TSS200\n",
+       "32      TP73        3  cg24073122  0.209996   TSS1500"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "input_path = (\n",
+    "     \"result/final_xzh/boruta_consensus_clustering_result_xzh_correct_cluster.csv\"   # example\n",
+    ")\n",
+    "final_gene = pd.read_csv(input_path)\n",
+    "# final_gene = pd.merge(final_gene, dbeta, on=\"gene\", how=\"inner\")\n",
+    "final_gene = final_gene[final_gene['dbeta'] > 0]\n",
+    "final_gene\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[['cg19157647', 'cg23631930', 'cg22746058', 'cg00213123'],\n",
+       " ['cg19157647', 'cg23631930', 'cg22746058', 'cg07552803'],\n",
+       " ['cg19157647', 'cg23631930', 'cg22746058', 'cg20248866'],\n",
+       " ['cg19157647', 'cg23631930', 'cg22746058', 'cg12610471'],\n",
+       " ['cg19157647', 'cg23631930', 'cg05884032', 'cg00213123'],\n",
+       " ['cg19157647', 'cg23631930', 'cg05884032', 'cg07552803'],\n",
+       " ['cg19157647', 'cg23631930', 'cg05884032', 'cg20248866'],\n",
+       " ['cg19157647', 'cg23631930', 'cg05884032', 'cg12610471'],\n",
+       " ['cg19157647', 'cg23631930', 'cg02547394', 'cg00213123'],\n",
+       " ['cg19157647', 'cg23631930', 'cg02547394', 'cg07552803'],\n",
+       " ['cg19157647', 'cg23631930', 'cg02547394', 'cg20248866'],\n",
+       " ['cg19157647', 'cg23631930', 'cg02547394', 'cg12610471'],\n",
+       " ['cg19157647', 'cg23631930', 'cg24073122', 'cg00213123'],\n",
+       " ['cg19157647', 'cg23631930', 'cg24073122', 'cg07552803'],\n",
+       " ['cg19157647', 'cg23631930', 'cg24073122', 'cg20248866'],\n",
+       " ['cg19157647', 'cg23631930', 'cg24073122', 'cg12610471'],\n",
+       " ['cg19157647', 'cg05724197', 'cg22746058', 'cg00213123'],\n",
+       " ['cg19157647', 'cg05724197', 'cg22746058', 'cg07552803'],\n",
+       " ['cg19157647', 'cg05724197', 'cg22746058', 'cg20248866'],\n",
+       " ['cg19157647', 'cg05724197', 'cg22746058', 'cg12610471'],\n",
+       " ['cg19157647', 'cg05724197', 'cg05884032', 'cg00213123'],\n",
+       " ['cg19157647', 'cg05724197', 'cg05884032', 'cg07552803'],\n",
+       " ['cg19157647', 'cg05724197', 'cg05884032', 'cg20248866'],\n",
+       " ['cg19157647', 'cg05724197', 'cg05884032', 'cg12610471'],\n",
+       " ['cg19157647', 'cg05724197', 'cg02547394', 'cg00213123'],\n",
+       " ['cg19157647', 'cg05724197', 'cg02547394', 'cg07552803'],\n",
+       " ['cg19157647', 'cg05724197', 'cg02547394', 'cg20248866'],\n",
+       " ['cg19157647', 'cg05724197', 'cg02547394', 'cg12610471'],\n",
+       " ['cg19157647', 'cg05724197', 'cg24073122', 'cg00213123'],\n",
+       " ['cg19157647', 'cg05724197', 'cg24073122', 'cg07552803'],\n",
+       " ['cg19157647', 'cg05724197', 'cg24073122', 'cg20248866'],\n",
+       " ['cg19157647', 'cg05724197', 'cg24073122', 'cg12610471'],\n",
+       " ['cg04927004', 'cg23631930', 'cg22746058', 'cg00213123'],\n",
+       " ['cg04927004', 'cg23631930', 'cg22746058', 'cg07552803'],\n",
+       " ['cg04927004', 'cg23631930', 'cg22746058', 'cg20248866'],\n",
+       " ['cg04927004', 'cg23631930', 'cg22746058', 'cg12610471'],\n",
+       " ['cg04927004', 'cg23631930', 'cg05884032', 'cg00213123'],\n",
+       " ['cg04927004', 'cg23631930', 'cg05884032', 'cg07552803'],\n",
+       " ['cg04927004', 'cg23631930', 'cg05884032', 'cg20248866'],\n",
+       " ['cg04927004', 'cg23631930', 'cg05884032', 'cg12610471'],\n",
+       " ['cg04927004', 'cg23631930', 'cg02547394', 'cg00213123'],\n",
+       " ['cg04927004', 'cg23631930', 'cg02547394', 'cg07552803'],\n",
+       " ['cg04927004', 'cg23631930', 'cg02547394', 'cg20248866'],\n",
+       " ['cg04927004', 'cg23631930', 'cg02547394', 'cg12610471'],\n",
+       " ['cg04927004', 'cg23631930', 'cg24073122', 'cg00213123'],\n",
+       " ['cg04927004', 'cg23631930', 'cg24073122', 'cg07552803'],\n",
+       " ['cg04927004', 'cg23631930', 'cg24073122', 'cg20248866'],\n",
+       " ['cg04927004', 'cg23631930', 'cg24073122', 'cg12610471'],\n",
+       " ['cg04927004', 'cg05724197', 'cg22746058', 'cg00213123'],\n",
+       " ['cg04927004', 'cg05724197', 'cg22746058', 'cg07552803'],\n",
+       " ['cg04927004', 'cg05724197', 'cg22746058', 'cg20248866'],\n",
+       " ['cg04927004', 'cg05724197', 'cg22746058', 'cg12610471'],\n",
+       " ['cg04927004', 'cg05724197', 'cg05884032', 'cg00213123'],\n",
+       " ['cg04927004', 'cg05724197', 'cg05884032', 'cg07552803'],\n",
+       " ['cg04927004', 'cg05724197', 'cg05884032', 'cg20248866'],\n",
+       " ['cg04927004', 'cg05724197', 'cg05884032', 'cg12610471'],\n",
+       " ['cg04927004', 'cg05724197', 'cg02547394', 'cg00213123'],\n",
+       " ['cg04927004', 'cg05724197', 'cg02547394', 'cg07552803'],\n",
+       " ['cg04927004', 'cg05724197', 'cg02547394', 'cg20248866'],\n",
+       " ['cg04927004', 'cg05724197', 'cg02547394', 'cg12610471'],\n",
+       " ['cg04927004', 'cg05724197', 'cg24073122', 'cg00213123'],\n",
+       " ['cg04927004', 'cg05724197', 'cg24073122', 'cg07552803'],\n",
+       " ['cg04927004', 'cg05724197', 'cg24073122', 'cg20248866'],\n",
+       " ['cg04927004', 'cg05724197', 'cg24073122', 'cg12610471']]"
+      ]
+     },
+     "execution_count": 97,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# 須包含ID和cluster欄位\n",
+    "\n",
+    "# 根據 Cluster 分組\n",
+    "import pandas as pd\n",
+    "import itertools\n",
+    "grouped = final_gene.groupby('cluster')\n",
+    "\n",
+    "# 生成排列組合\n",
+    "combinations = list(itertools.product(*[group.values.tolist() for _, group in grouped]))\n",
+    "# print(combinations)\n",
+    "# 將結果轉換為所需格式\n",
+    "result = []\n",
+    "for combo in combinations:\n",
+    "    result.append([row[3] for row in combo])  # row[0] 對應的是 Gene 列\n",
+    "\n",
+    "cg_list = result\n",
+    "cg_list"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Model</th>\n",
+       "      <th>ID1</th>\n",
+       "      <th>ID2</th>\n",
+       "      <th>ID3</th>\n",
+       "      <th>ID4</th>\n",
+       "      <th>train_accuracy</th>\n",
+       "      <th>test_accuracy</th>\n",
+       "      <th>train - test accuracy</th>\n",
+       "      <th>AUC</th>\n",
+       "      <th>f1-score</th>\n",
+       "      <th>sensitivity</th>\n",
+       "      <th>specificity</th>\n",
+       "      <th>precision</th>\n",
+       "      <th>mcc</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Decision Tree</td>\n",
+       "      <td>cg19157647</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>cg22746058</td>\n",
+       "      <td>cg00213123</td>\n",
+       "      <td>0.671233</td>\n",
+       "      <td>0.368421</td>\n",
+       "      <td>0.302812</td>\n",
+       "      <td>0.350000</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>0.111111</td>\n",
+       "      <td>0.6</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>-0.327569</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Logistic Regression</td>\n",
+       "      <td>cg19157647</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>cg22746058</td>\n",
+       "      <td>cg00213123</td>\n",
+       "      <td>0.506849</td>\n",
+       "      <td>0.473684</td>\n",
+       "      <td>0.033165</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.642857</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.473684</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Random Forest</td>\n",
+       "      <td>cg19157647</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>cg22746058</td>\n",
+       "      <td>cg00213123</td>\n",
+       "      <td>0.698630</td>\n",
+       "      <td>0.315789</td>\n",
+       "      <td>0.382841</td>\n",
+       "      <td>0.311111</td>\n",
+       "      <td>0.380952</td>\n",
+       "      <td>0.444444</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>-0.368035</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>SVM</td>\n",
+       "      <td>cg19157647</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>cg22746058</td>\n",
+       "      <td>cg00213123</td>\n",
+       "      <td>0.506849</td>\n",
+       "      <td>0.473684</td>\n",
+       "      <td>0.033165</td>\n",
+       "      <td>0.422222</td>\n",
+       "      <td>0.642857</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.473684</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>XGBoost</td>\n",
+       "      <td>cg19157647</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>cg22746058</td>\n",
+       "      <td>cg00213123</td>\n",
+       "      <td>0.876712</td>\n",
+       "      <td>0.368421</td>\n",
+       "      <td>0.508291</td>\n",
+       "      <td>0.294444</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.7</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-0.410792</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>315</th>\n",
+       "      <td>Decision Tree</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>cg24073122</td>\n",
+       "      <td>cg12610471</td>\n",
+       "      <td>0.698630</td>\n",
+       "      <td>0.526316</td>\n",
+       "      <td>0.172314</td>\n",
+       "      <td>0.633333</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.7</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.035806</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>316</th>\n",
+       "      <td>Logistic Regression</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>cg24073122</td>\n",
+       "      <td>cg12610471</td>\n",
+       "      <td>0.506849</td>\n",
+       "      <td>0.473684</td>\n",
+       "      <td>0.033165</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.642857</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.473684</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>317</th>\n",
+       "      <td>Random Forest</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>cg24073122</td>\n",
+       "      <td>cg12610471</td>\n",
+       "      <td>0.972603</td>\n",
+       "      <td>0.631579</td>\n",
+       "      <td>0.341024</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>0.631579</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.6</td>\n",
+       "      <td>0.600000</td>\n",
+       "      <td>0.266667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>318</th>\n",
+       "      <td>SVM</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>cg24073122</td>\n",
+       "      <td>cg12610471</td>\n",
+       "      <td>0.575342</td>\n",
+       "      <td>0.631579</td>\n",
+       "      <td>-0.056236</td>\n",
+       "      <td>0.388889</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.777778</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.583333</td>\n",
+       "      <td>0.287527</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>319</th>\n",
+       "      <td>XGBoost</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>cg24073122</td>\n",
+       "      <td>cg12610471</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.578947</td>\n",
+       "      <td>0.421053</td>\n",
+       "      <td>0.622222</td>\n",
+       "      <td>0.555556</td>\n",
+       "      <td>0.555556</td>\n",
+       "      <td>0.6</td>\n",
+       "      <td>0.555556</td>\n",
+       "      <td>0.155556</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>320 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   Model         ID1         ID2         ID3         ID4  \\\n",
+       "0          Decision Tree  cg19157647  cg23631930  cg22746058  cg00213123   \n",
+       "1    Logistic Regression  cg19157647  cg23631930  cg22746058  cg00213123   \n",
+       "2          Random Forest  cg19157647  cg23631930  cg22746058  cg00213123   \n",
+       "3                    SVM  cg19157647  cg23631930  cg22746058  cg00213123   \n",
+       "4                XGBoost  cg19157647  cg23631930  cg22746058  cg00213123   \n",
+       "..                   ...         ...         ...         ...         ...   \n",
+       "315        Decision Tree  cg04927004  cg05724197  cg24073122  cg12610471   \n",
+       "316  Logistic Regression  cg04927004  cg05724197  cg24073122  cg12610471   \n",
+       "317        Random Forest  cg04927004  cg05724197  cg24073122  cg12610471   \n",
+       "318                  SVM  cg04927004  cg05724197  cg24073122  cg12610471   \n",
+       "319              XGBoost  cg04927004  cg05724197  cg24073122  cg12610471   \n",
+       "\n",
+       "     train_accuracy  test_accuracy  train - test accuracy       AUC  f1-score  \\\n",
+       "0          0.671233       0.368421               0.302812  0.350000  0.142857   \n",
+       "1          0.506849       0.473684               0.033165  0.666667  0.642857   \n",
+       "2          0.698630       0.315789               0.382841  0.311111  0.380952   \n",
+       "3          0.506849       0.473684               0.033165  0.422222  0.642857   \n",
+       "4          0.876712       0.368421               0.508291  0.294444  0.000000   \n",
+       "..              ...            ...                    ...       ...       ...   \n",
+       "315        0.698630       0.526316               0.172314  0.633333  0.400000   \n",
+       "316        0.506849       0.473684               0.033165  0.500000  0.642857   \n",
+       "317        0.972603       0.631579               0.341024  0.733333  0.631579   \n",
+       "318        0.575342       0.631579              -0.056236  0.388889  0.666667   \n",
+       "319        1.000000       0.578947               0.421053  0.622222  0.555556   \n",
+       "\n",
+       "     sensitivity  specificity  precision       mcc  \n",
+       "0       0.111111          0.6   0.200000 -0.327569  \n",
+       "1       1.000000          0.0   0.473684  0.000000  \n",
+       "2       0.444444          0.2   0.333333 -0.368035  \n",
+       "3       1.000000          0.0   0.473684  0.000000  \n",
+       "4       0.000000          0.7   0.000000 -0.410792  \n",
+       "..           ...          ...        ...       ...  \n",
+       "315     0.333333          0.7   0.500000  0.035806  \n",
+       "316     1.000000          0.0   0.473684  0.000000  \n",
+       "317     0.666667          0.6   0.600000  0.266667  \n",
+       "318     0.777778          0.5   0.583333  0.287527  \n",
+       "319     0.555556          0.6   0.555556  0.155556  \n",
+       "\n",
+       "[320 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 99,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "from sklearn.svm import SVC\n",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "import xgboost as xgb\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.metrics import classification_report, roc_auc_score, accuracy_score, precision_score, recall_score, f1_score\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from xgboost import XGBClassifier\n",
+    "from sklearn.model_selection import RandomizedSearchCV\n",
+    "from sklearn.model_selection import GridSearchCV\n",
+    "from skopt import BayesSearchCV\n",
+    "from skopt.space import Categorical, Real\n",
+    "from sklearn.metrics import (\n",
+    "    confusion_matrix,\n",
+    "    precision_score,\n",
+    "    accuracy_score,\n",
+    "    matthews_corrcoef,\n",
+    "    f1_score,\n",
+    ")\n",
+    "\n",
+    "\n",
+    "tree_params = {\"max_depth\": [3, 5, 7], \"min_samples_split\": [2, 5, 10]}\n",
+    "\n",
+    "clf_tree = DecisionTreeClassifier()\n",
+    "\n",
+    "lr_params = [\n",
+    "   {\"C\": [0.001,0.01,0.1, 1, 10], \"solver\": [\"liblinear\"]}\n",
+    "]\n",
+    "\n",
+    "clf_lr = LogisticRegression(max_iter=500) \n",
+    "\n",
+    "\n",
+    "rf_params = {\n",
+    "        \"n_estimators\": [100,150, 200],\n",
+    "        \"max_depth\": [1,3, 5, 7],\n",
+    "        \"min_samples_split\": [2, 5, 10],\n",
+    "    }\n",
+    "clf_rf = RandomForestClassifier()\n",
+    "\n",
+    "svm_params = {\"C\": [0.001,0.1, 1, 10,100,1000], \"kernel\": [\"linear\", \"rbf\"]}\n",
+    "\n",
+    "clf_svm = SVC(probability=True)\n",
+    "\n",
+    "\n",
+    "xgb_params = {\n",
+    "        \"n_estimators\": [100,150, 200],\n",
+    "        \"max_depth\": [3, 5, 7],\n",
+    "        \"learning_rate\": [0.01, 0.1, 0.2],\n",
+    "    }\n",
+    "\n",
+    "clf_xgb = XGBClassifier( eval_metric='logloss')\n",
+    "\n",
+    "results = []\n",
+    "\n",
+    "model_list = [clf_tree,clf_lr,clf_rf,clf_svm,clf_xgb]\n",
+    "model_param = [tree_params,lr_params,rf_params,svm_params,xgb_params]\n",
+    "model_names = ['Decision Tree', 'Logistic Regression', 'Random Forest', 'SVM', 'XGBoost']\n",
+    "\n",
+    "for cg in cg_list:\n",
+    "    X_train_c = X_train[cg]\n",
+    "    X_test_c = X_test[cg]\n",
+    "    \n",
+    "    for model,param, model_name in zip(model_list,model_param, model_names):\n",
+    "        \n",
+    "        model = GridSearchCV(\n",
+    "                    estimator=model, param_grid=param, cv=5, n_jobs=-1\n",
+    "        )\n",
+    "        model.fit(X_train_c, y_train)\n",
+    "        \n",
+    "        y_pred = model.predict(X_test_c)\n",
+    "        y_pred_prob = model.predict_proba(X_test_c)[:, 1]\n",
+    "        \n",
+    "        y_pred_train = model.predict(X_train_c)\n",
+    "        y_pred_prob_train = model.predict_proba(X_train_c)[:, 1]\n",
+    "        # report = classification_report(y_test, y_pred, output_dict=True)\n",
+    "        auc = roc_auc_score(y_test, y_pred_prob)\n",
+    "        \n",
+    "        train_accuracy = accuracy_score(y_train, y_pred_train)\n",
+    "        test_accuracy = accuracy_score(y_test, y_pred)\n",
+    "        precision = precision_score(y_test, y_pred,zero_division=0)\n",
+    "        sensitivity = recall_score(y_test, y_pred)\n",
+    "        specificity = recall_score(y_test, y_pred, pos_label=0)\n",
+    "        f1 = f1_score(y_test, y_pred)\n",
+    "        mcc = matthews_corrcoef(y_test, y_pred)\n",
+    "\n",
+    "\n",
+    "        # 計算複合指標\\\n",
+    "        \n",
+    "        results.append( {\n",
+    "            'Model': model_name,\n",
+    "            'ID1': cg[0],\n",
+    "            'ID2': cg[1],\n",
+    "            'ID3': cg[2],\n",
+    "            'ID4': cg[3],\n",
+    "            'train_accuracy': train_accuracy,\n",
+    "            'test_accuracy': test_accuracy,\n",
+    "            'train - test accuracy' : train_accuracy - test_accuracy,\n",
+    "            'AUC': auc,\n",
+    "            'f1-score': f1,\n",
+    "            'sensitivity': sensitivity,\n",
+    "            'specificity': specificity,\n",
+    "            'precision': precision,\n",
+    "            'mcc' : mcc\n",
+    "        })\n",
+    "df = pd.DataFrame(results)\n",
+    "\n",
+    "df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "df.to_csv(\"result/test_aba2/5_fold_GSE89093_hyper.csv\",index=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 148663"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 130,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>55</th>\n",
+       "      <th>56</th>\n",
+       "      <th>57</th>\n",
+       "      <th>58</th>\n",
+       "      <th>59</th>\n",
+       "      <th>60</th>\n",
+       "      <th>61</th>\n",
+       "      <th>62</th>\n",
+       "      <th>63</th>\n",
+       "      <th>64</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg00000957</td>\n",
+       "      <td>0.860452</td>\n",
+       "      <td>0.860452</td>\n",
+       "      <td>0.849385</td>\n",
+       "      <td>0.849385</td>\n",
+       "      <td>0.834130</td>\n",
+       "      <td>0.834130</td>\n",
+       "      <td>0.850606</td>\n",
+       "      <td>0.850606</td>\n",
+       "      <td>0.861816</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.829853</td>\n",
+       "      <td>0.829853</td>\n",
+       "      <td>0.858515</td>\n",
+       "      <td>0.858515</td>\n",
+       "      <td>0.843767</td>\n",
+       "      <td>0.843767</td>\n",
+       "      <td>0.827038</td>\n",
+       "      <td>0.827038</td>\n",
+       "      <td>0.824223</td>\n",
+       "      <td>0.824223</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg00001349</td>\n",
+       "      <td>0.651237</td>\n",
+       "      <td>0.651237</td>\n",
+       "      <td>0.732471</td>\n",
+       "      <td>0.732471</td>\n",
+       "      <td>0.650520</td>\n",
+       "      <td>0.650520</td>\n",
+       "      <td>0.714359</td>\n",
+       "      <td>0.714359</td>\n",
+       "      <td>0.689401</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.743716</td>\n",
+       "      <td>0.743716</td>\n",
+       "      <td>0.740031</td>\n",
+       "      <td>0.740031</td>\n",
+       "      <td>0.735415</td>\n",
+       "      <td>0.735415</td>\n",
+       "      <td>0.691370</td>\n",
+       "      <td>0.691370</td>\n",
+       "      <td>0.641379</td>\n",
+       "      <td>0.641379</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg00001583</td>\n",
+       "      <td>0.105578</td>\n",
+       "      <td>0.105578</td>\n",
+       "      <td>0.151054</td>\n",
+       "      <td>0.151054</td>\n",
+       "      <td>0.137455</td>\n",
+       "      <td>0.137455</td>\n",
+       "      <td>0.138043</td>\n",
+       "      <td>0.138043</td>\n",
+       "      <td>0.145586</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.149378</td>\n",
+       "      <td>0.149378</td>\n",
+       "      <td>0.127976</td>\n",
+       "      <td>0.127976</td>\n",
+       "      <td>0.133689</td>\n",
+       "      <td>0.133689</td>\n",
+       "      <td>0.146530</td>\n",
+       "      <td>0.146530</td>\n",
+       "      <td>0.139891</td>\n",
+       "      <td>0.139891</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg00002028</td>\n",
+       "      <td>0.089119</td>\n",
+       "      <td>0.089119</td>\n",
+       "      <td>0.095975</td>\n",
+       "      <td>0.095975</td>\n",
+       "      <td>0.092523</td>\n",
+       "      <td>0.092523</td>\n",
+       "      <td>0.098960</td>\n",
+       "      <td>0.098960</td>\n",
+       "      <td>0.081822</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.115429</td>\n",
+       "      <td>0.115429</td>\n",
+       "      <td>0.135141</td>\n",
+       "      <td>0.135141</td>\n",
+       "      <td>0.113261</td>\n",
+       "      <td>0.113261</td>\n",
+       "      <td>0.117921</td>\n",
+       "      <td>0.117921</td>\n",
+       "      <td>0.107023</td>\n",
+       "      <td>0.107023</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg00002719</td>\n",
+       "      <td>0.055126</td>\n",
+       "      <td>0.055126</td>\n",
+       "      <td>0.050742</td>\n",
+       "      <td>0.050742</td>\n",
+       "      <td>0.070888</td>\n",
+       "      <td>0.070888</td>\n",
+       "      <td>0.061152</td>\n",
+       "      <td>0.061152</td>\n",
+       "      <td>0.066180</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.052978</td>\n",
+       "      <td>0.052978</td>\n",
+       "      <td>0.052756</td>\n",
+       "      <td>0.052756</td>\n",
+       "      <td>0.049943</td>\n",
+       "      <td>0.049943</td>\n",
+       "      <td>0.060414</td>\n",
+       "      <td>0.060414</td>\n",
+       "      <td>0.060297</td>\n",
+       "      <td>0.060297</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>410742</th>\n",
+       "      <td>cg27656573</td>\n",
+       "      <td>0.944012</td>\n",
+       "      <td>0.944012</td>\n",
+       "      <td>0.944695</td>\n",
+       "      <td>0.944695</td>\n",
+       "      <td>0.936954</td>\n",
+       "      <td>0.936954</td>\n",
+       "      <td>0.931952</td>\n",
+       "      <td>0.931952</td>\n",
+       "      <td>0.943306</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.939021</td>\n",
+       "      <td>0.939021</td>\n",
+       "      <td>0.934166</td>\n",
+       "      <td>0.934166</td>\n",
+       "      <td>0.935279</td>\n",
+       "      <td>0.935279</td>\n",
+       "      <td>0.923842</td>\n",
+       "      <td>0.923842</td>\n",
+       "      <td>0.937656</td>\n",
+       "      <td>0.937656</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>410743</th>\n",
+       "      <td>cg27657363</td>\n",
+       "      <td>0.879266</td>\n",
+       "      <td>0.879266</td>\n",
+       "      <td>0.864261</td>\n",
+       "      <td>0.864261</td>\n",
+       "      <td>0.878780</td>\n",
+       "      <td>0.878780</td>\n",
+       "      <td>0.862390</td>\n",
+       "      <td>0.862390</td>\n",
+       "      <td>0.900482</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.872920</td>\n",
+       "      <td>0.872920</td>\n",
+       "      <td>0.855532</td>\n",
+       "      <td>0.855532</td>\n",
+       "      <td>0.865387</td>\n",
+       "      <td>0.865387</td>\n",
+       "      <td>0.847414</td>\n",
+       "      <td>0.847414</td>\n",
+       "      <td>0.849145</td>\n",
+       "      <td>0.849145</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>410744</th>\n",
+       "      <td>cg27657537</td>\n",
+       "      <td>0.081713</td>\n",
+       "      <td>0.081713</td>\n",
+       "      <td>0.131523</td>\n",
+       "      <td>0.131523</td>\n",
+       "      <td>0.103004</td>\n",
+       "      <td>0.103004</td>\n",
+       "      <td>0.109616</td>\n",
+       "      <td>0.109616</td>\n",
+       "      <td>0.098497</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.111502</td>\n",
+       "      <td>0.111502</td>\n",
+       "      <td>0.104687</td>\n",
+       "      <td>0.104687</td>\n",
+       "      <td>0.116231</td>\n",
+       "      <td>0.116231</td>\n",
+       "      <td>0.131304</td>\n",
+       "      <td>0.131304</td>\n",
+       "      <td>0.085185</td>\n",
+       "      <td>0.085185</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>410745</th>\n",
+       "      <td>cg27662611</td>\n",
+       "      <td>0.094778</td>\n",
+       "      <td>0.094778</td>\n",
+       "      <td>0.064147</td>\n",
+       "      <td>0.064147</td>\n",
+       "      <td>0.097572</td>\n",
+       "      <td>0.097572</td>\n",
+       "      <td>0.086322</td>\n",
+       "      <td>0.086322</td>\n",
+       "      <td>0.085894</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.061859</td>\n",
+       "      <td>0.061859</td>\n",
+       "      <td>0.066906</td>\n",
+       "      <td>0.066906</td>\n",
+       "      <td>0.077438</td>\n",
+       "      <td>0.077438</td>\n",
+       "      <td>0.063476</td>\n",
+       "      <td>0.063476</td>\n",
+       "      <td>0.072437</td>\n",
+       "      <td>0.072437</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>410746</th>\n",
+       "      <td>cg27665648</td>\n",
+       "      <td>0.905899</td>\n",
+       "      <td>0.905899</td>\n",
+       "      <td>0.879893</td>\n",
+       "      <td>0.879893</td>\n",
+       "      <td>0.885073</td>\n",
+       "      <td>0.885073</td>\n",
+       "      <td>0.874895</td>\n",
+       "      <td>0.874895</td>\n",
+       "      <td>0.883834</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.870525</td>\n",
+       "      <td>0.870525</td>\n",
+       "      <td>0.885072</td>\n",
+       "      <td>0.885072</td>\n",
+       "      <td>0.876430</td>\n",
+       "      <td>0.876430</td>\n",
+       "      <td>0.893851</td>\n",
+       "      <td>0.893851</td>\n",
+       "      <td>0.855568</td>\n",
+       "      <td>0.855568</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>410747 rows × 65 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unnamed: 0         1         2         3         4         5  \\\n",
+       "0       cg00000957  0.860452  0.860452  0.849385  0.849385  0.834130   \n",
+       "1       cg00001349  0.651237  0.651237  0.732471  0.732471  0.650520   \n",
+       "2       cg00001583  0.105578  0.105578  0.151054  0.151054  0.137455   \n",
+       "3       cg00002028  0.089119  0.089119  0.095975  0.095975  0.092523   \n",
+       "4       cg00002719  0.055126  0.055126  0.050742  0.050742  0.070888   \n",
+       "...            ...       ...       ...       ...       ...       ...   \n",
+       "410742  cg27656573  0.944012  0.944012  0.944695  0.944695  0.936954   \n",
+       "410743  cg27657363  0.879266  0.879266  0.864261  0.864261  0.878780   \n",
+       "410744  cg27657537  0.081713  0.081713  0.131523  0.131523  0.103004   \n",
+       "410745  cg27662611  0.094778  0.094778  0.064147  0.064147  0.097572   \n",
+       "410746  cg27665648  0.905899  0.905899  0.879893  0.879893  0.885073   \n",
+       "\n",
+       "               6         7         8         9  ...        55        56  \\\n",
+       "0       0.834130  0.850606  0.850606  0.861816  ...  0.829853  0.829853   \n",
+       "1       0.650520  0.714359  0.714359  0.689401  ...  0.743716  0.743716   \n",
+       "2       0.137455  0.138043  0.138043  0.145586  ...  0.149378  0.149378   \n",
+       "3       0.092523  0.098960  0.098960  0.081822  ...  0.115429  0.115429   \n",
+       "4       0.070888  0.061152  0.061152  0.066180  ...  0.052978  0.052978   \n",
+       "...          ...       ...       ...       ...  ...       ...       ...   \n",
+       "410742  0.936954  0.931952  0.931952  0.943306  ...  0.939021  0.939021   \n",
+       "410743  0.878780  0.862390  0.862390  0.900482  ...  0.872920  0.872920   \n",
+       "410744  0.103004  0.109616  0.109616  0.098497  ...  0.111502  0.111502   \n",
+       "410745  0.097572  0.086322  0.086322  0.085894  ...  0.061859  0.061859   \n",
+       "410746  0.885073  0.874895  0.874895  0.883834  ...  0.870525  0.870525   \n",
+       "\n",
+       "              57        58        59        60        61        62        63  \\\n",
+       "0       0.858515  0.858515  0.843767  0.843767  0.827038  0.827038  0.824223   \n",
+       "1       0.740031  0.740031  0.735415  0.735415  0.691370  0.691370  0.641379   \n",
+       "2       0.127976  0.127976  0.133689  0.133689  0.146530  0.146530  0.139891   \n",
+       "3       0.135141  0.135141  0.113261  0.113261  0.117921  0.117921  0.107023   \n",
+       "4       0.052756  0.052756  0.049943  0.049943  0.060414  0.060414  0.060297   \n",
+       "...          ...       ...       ...       ...       ...       ...       ...   \n",
+       "410742  0.934166  0.934166  0.935279  0.935279  0.923842  0.923842  0.937656   \n",
+       "410743  0.855532  0.855532  0.865387  0.865387  0.847414  0.847414  0.849145   \n",
+       "410744  0.104687  0.104687  0.116231  0.116231  0.131304  0.131304  0.085185   \n",
+       "410745  0.066906  0.066906  0.077438  0.077438  0.063476  0.063476  0.072437   \n",
+       "410746  0.885072  0.885072  0.876430  0.876430  0.893851  0.893851  0.855568   \n",
+       "\n",
+       "              64  \n",
+       "0       0.824223  \n",
+       "1       0.641379  \n",
+       "2       0.139891  \n",
+       "3       0.107023  \n",
+       "4       0.060297  \n",
+       "...          ...  \n",
+       "410742  0.937656  \n",
+       "410743  0.849145  \n",
+       "410744  0.085185  \n",
+       "410745  0.072437  \n",
+       "410746  0.855568  \n",
+       "\n",
+       "[410747 rows x 65 columns]"
+      ]
+     },
+     "execution_count": 130,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "beta_normalized_148663 = \"source/GSE148663/all_beta_normalized_breast_liquid.csv\" #使用無oversampling之原始資料\n",
+    "data_148663 = pd.read_csv(beta_normalized_148663)\n",
+    "data_148663"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 131,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>cg12440062</th>\n",
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+       "      <td>...</td>\n",
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+       "      <td>0.796604</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg26106778</th>\n",
+       "      <td>0.339627</td>\n",
+       "      <td>0.333992</td>\n",
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+       "      <td>0.297169</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg22746058</th>\n",
+       "      <td>0.240843</td>\n",
+       "      <td>0.214881</td>\n",
+       "      <td>0.208892</td>\n",
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+       "      <td>0.189155</td>\n",
+       "      <td>0.209402</td>\n",
+       "      <td>0.188544</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg11775521</th>\n",
+       "      <td>0.340537</td>\n",
+       "      <td>0.374279</td>\n",
+       "      <td>0.333575</td>\n",
+       "      <td>0.382166</td>\n",
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+       "      <td>0.509974</td>\n",
+       "      <td>0.498385</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>0.396511</td>\n",
+       "      <td>0.353510</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg05724197</th>\n",
+       "      <td>0.756970</td>\n",
+       "      <td>0.744442</td>\n",
+       "      <td>0.817312</td>\n",
+       "      <td>0.738567</td>\n",
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+       "      <td>0.708666</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>0.726985</td>\n",
+       "      <td>0.803037</td>\n",
+       "      <td>0.746333</td>\n",
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+       "      <td>0.723885</td>\n",
+       "      <td>0.725921</td>\n",
+       "      <td>0.699362</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg05884032</th>\n",
+       "      <td>0.140366</td>\n",
+       "      <td>0.153582</td>\n",
+       "      <td>0.117149</td>\n",
+       "      <td>0.153837</td>\n",
+       "      <td>0.153574</td>\n",
+       "      <td>0.136523</td>\n",
+       "      <td>0.143567</td>\n",
+       "      <td>0.101803</td>\n",
+       "      <td>0.132475</td>\n",
+       "      <td>0.167759</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.115206</td>\n",
+       "      <td>0.125056</td>\n",
+       "      <td>0.128294</td>\n",
+       "      <td>0.157506</td>\n",
+       "      <td>0.101866</td>\n",
+       "      <td>0.167934</td>\n",
+       "      <td>0.127974</td>\n",
+       "      <td>0.146776</td>\n",
+       "      <td>0.138478</td>\n",
+       "      <td>0.156235</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg04927004</th>\n",
+       "      <td>0.329177</td>\n",
+       "      <td>0.362840</td>\n",
+       "      <td>0.331304</td>\n",
+       "      <td>0.295751</td>\n",
+       "      <td>0.317637</td>\n",
+       "      <td>0.298596</td>\n",
+       "      <td>0.419554</td>\n",
+       "      <td>0.323678</td>\n",
+       "      <td>0.374353</td>\n",
+       "      <td>0.349252</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.335540</td>\n",
+       "      <td>0.329450</td>\n",
+       "      <td>0.308986</td>\n",
+       "      <td>0.291237</td>\n",
+       "      <td>0.272521</td>\n",
+       "      <td>0.323200</td>\n",
+       "      <td>0.303031</td>\n",
+       "      <td>0.310586</td>\n",
+       "      <td>0.315241</td>\n",
+       "      <td>0.296926</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg07211259</th>\n",
+       "      <td>0.308566</td>\n",
+       "      <td>0.229945</td>\n",
+       "      <td>0.379668</td>\n",
+       "      <td>0.159407</td>\n",
+       "      <td>0.274011</td>\n",
+       "      <td>0.303563</td>\n",
+       "      <td>0.309349</td>\n",
+       "      <td>0.196633</td>\n",
+       "      <td>0.330686</td>\n",
+       "      <td>0.340288</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.303235</td>\n",
+       "      <td>0.340761</td>\n",
+       "      <td>0.351834</td>\n",
+       "      <td>0.271578</td>\n",
+       "      <td>0.216020</td>\n",
+       "      <td>0.196694</td>\n",
+       "      <td>0.226154</td>\n",
+       "      <td>0.293970</td>\n",
+       "      <td>0.268459</td>\n",
+       "      <td>0.322834</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg04225088</th>\n",
+       "      <td>0.646110</td>\n",
+       "      <td>0.664724</td>\n",
+       "      <td>0.602769</td>\n",
+       "      <td>0.743808</td>\n",
+       "      <td>0.699191</td>\n",
+       "      <td>0.754460</td>\n",
+       "      <td>0.871858</td>\n",
+       "      <td>0.820077</td>\n",
+       "      <td>0.815631</td>\n",
+       "      <td>0.831151</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.663412</td>\n",
+       "      <td>0.605783</td>\n",
+       "      <td>0.661702</td>\n",
+       "      <td>0.426238</td>\n",
+       "      <td>0.624397</td>\n",
+       "      <td>0.677641</td>\n",
+       "      <td>0.672440</td>\n",
+       "      <td>0.719282</td>\n",
+       "      <td>0.620109</td>\n",
+       "      <td>0.658940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cg23631930</th>\n",
+       "      <td>0.866250</td>\n",
+       "      <td>0.853623</td>\n",
+       "      <td>0.865487</td>\n",
+       "      <td>0.851834</td>\n",
+       "      <td>0.869477</td>\n",
+       "      <td>0.883931</td>\n",
+       "      <td>0.829180</td>\n",
+       "      <td>0.866920</td>\n",
+       "      <td>0.822805</td>\n",
+       "      <td>0.844901</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.877658</td>\n",
+       "      <td>0.857388</td>\n",
+       "      <td>0.862686</td>\n",
+       "      <td>0.861214</td>\n",
+       "      <td>0.841907</td>\n",
+       "      <td>0.848497</td>\n",
+       "      <td>0.860156</td>\n",
+       "      <td>0.855846</td>\n",
+       "      <td>0.842887</td>\n",
+       "      <td>0.853995</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10 rows × 32 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   1         3         5         7         9        11  \\\n",
+       "Unnamed: 0                                                               \n",
+       "cg12440062  0.678392  0.736543  0.529423  0.750610  0.447820  0.685264   \n",
+       "cg26106778  0.339627  0.333992  0.298333  0.354617  0.321448  0.350549   \n",
+       "cg22746058  0.240843  0.214881  0.208892  0.220645  0.258942  0.139600   \n",
+       "cg11775521  0.340537  0.374279  0.333575  0.382166  0.363007  0.392132   \n",
+       "cg05724197  0.756970  0.744442  0.817312  0.738567  0.812436  0.767983   \n",
+       "cg05884032  0.140366  0.153582  0.117149  0.153837  0.153574  0.136523   \n",
+       "cg04927004  0.329177  0.362840  0.331304  0.295751  0.317637  0.298596   \n",
+       "cg07211259  0.308566  0.229945  0.379668  0.159407  0.274011  0.303563   \n",
+       "cg04225088  0.646110  0.664724  0.602769  0.743808  0.699191  0.754460   \n",
+       "cg23631930  0.866250  0.853623  0.865487  0.851834  0.869477  0.883931   \n",
+       "\n",
+       "                  13        15        17        19  ...        45        47  \\\n",
+       "Unnamed: 0                                          ...                       \n",
+       "cg12440062  0.679293  0.807414  0.783905  0.578240  ...  0.714003  0.681126   \n",
+       "cg26106778  0.457564  0.409579  0.425081  0.375744  ...  0.297637  0.315604   \n",
+       "cg22746058  0.252646  0.294675  0.266106  0.283940  ...  0.186870  0.211662   \n",
+       "cg11775521  0.580303  0.472013  0.509974  0.498385  ...  0.369552  0.341304   \n",
+       "cg05724197  0.639979  0.743354  0.708666  0.725989  ...  0.766350  0.726985   \n",
+       "cg05884032  0.143567  0.101803  0.132475  0.167759  ...  0.115206  0.125056   \n",
+       "cg04927004  0.419554  0.323678  0.374353  0.349252  ...  0.335540  0.329450   \n",
+       "cg07211259  0.309349  0.196633  0.330686  0.340288  ...  0.303235  0.340761   \n",
+       "cg04225088  0.871858  0.820077  0.815631  0.831151  ...  0.663412  0.605783   \n",
+       "cg23631930  0.829180  0.866920  0.822805  0.844901  ...  0.877658  0.857388   \n",
+       "\n",
+       "                  49        51        53        55        57        59  \\\n",
+       "Unnamed: 0                                                               \n",
+       "cg12440062  0.767368  0.735547  0.663974  0.816347  0.755333  0.691331   \n",
+       "cg26106778  0.331447  0.255999  0.327556  0.353310  0.375039  0.360041   \n",
+       "cg22746058  0.137534  0.162651  0.153817  0.185828  0.161554  0.189155   \n",
+       "cg11775521  0.396885  0.220624  0.364626  0.436315  0.432447  0.435344   \n",
+       "cg05724197  0.803037  0.746333  0.733456  0.737862  0.739196  0.723885   \n",
+       "cg05884032  0.128294  0.157506  0.101866  0.167934  0.127974  0.146776   \n",
+       "cg04927004  0.308986  0.291237  0.272521  0.323200  0.303031  0.310586   \n",
+       "cg07211259  0.351834  0.271578  0.216020  0.196694  0.226154  0.293970   \n",
+       "cg04225088  0.661702  0.426238  0.624397  0.677641  0.672440  0.719282   \n",
+       "cg23631930  0.862686  0.861214  0.841907  0.848497  0.860156  0.855846   \n",
+       "\n",
+       "                  61        63  \n",
+       "Unnamed: 0                      \n",
+       "cg12440062  0.610272  0.796604  \n",
+       "cg26106778  0.340470  0.297169  \n",
+       "cg22746058  0.209402  0.188544  \n",
+       "cg11775521  0.396511  0.353510  \n",
+       "cg05724197  0.725921  0.699362  \n",
+       "cg05884032  0.138478  0.156235  \n",
+       "cg04927004  0.315241  0.296926  \n",
+       "cg07211259  0.268459  0.322834  \n",
+       "cg04225088  0.620109  0.658940  \n",
+       "cg23631930  0.842887  0.853995  \n",
+       "\n",
+       "[10 rows x 32 columns]"
+      ]
+     },
+     "execution_count": 131,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y_test_148663 = [(0 if i < 10 else 1) for i in range(32)]\n",
+    "\n",
+    "# 檢查挑選出的特徵是否都有出現\n",
+    "\n",
+    "data_148663 = data_148663[data_148663[\"Unnamed: 0\"].isin(final_gene[\"ID\"])]\n",
+    "\n",
+    "data_148663.set_index(\"Unnamed: 0\", inplace=True)\n",
+    "\n",
+    "data_148663 = data_148663.iloc[:, ::2]\n",
+    "# data_450K = pd.merge(data_450K_0, data_450K_1, on=\"Unnamed: 0\")\n",
+    "data_148663"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 132,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "訓練集類別分佈:\n",
+      "   Class  Count  Percentage\n",
+      "0      0      8        32.0\n",
+      "1      1     17        68.0\n",
+      "\n",
+      "測試集類別分佈:\n",
+      "   Class  Count  Percentage\n",
+      "0      0      2   28.571429\n",
+      "1      1      5   71.428571\n",
+      "\n",
+      "訓練集和測試集的大小:\n",
+      "訓練集大小: 25\n",
+      "測試集大小: 7\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>cg12440062</th>\n",
+       "      <th>cg26106778</th>\n",
+       "      <th>cg22746058</th>\n",
+       "      <th>cg11775521</th>\n",
+       "      <th>cg05724197</th>\n",
+       "      <th>cg05884032</th>\n",
+       "      <th>cg04927004</th>\n",
+       "      <th>cg07211259</th>\n",
+       "      <th>cg04225088</th>\n",
+       "      <th>cg23631930</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>0.735547</td>\n",
+       "      <td>0.255999</td>\n",
+       "      <td>0.162651</td>\n",
+       "      <td>0.220624</td>\n",
+       "      <td>0.746333</td>\n",
+       "      <td>0.157506</td>\n",
+       "      <td>0.291237</td>\n",
+       "      <td>0.271578</td>\n",
+       "      <td>0.426238</td>\n",
+       "      <td>0.861214</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>0.813720</td>\n",
+       "      <td>0.269805</td>\n",
+       "      <td>0.134080</td>\n",
+       "      <td>0.282190</td>\n",
+       "      <td>0.789789</td>\n",
+       "      <td>0.132311</td>\n",
+       "      <td>0.311697</td>\n",
+       "      <td>0.212900</td>\n",
+       "      <td>0.477628</td>\n",
+       "      <td>0.867339</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.678392</td>\n",
+       "      <td>0.339627</td>\n",
+       "      <td>0.240843</td>\n",
+       "      <td>0.340537</td>\n",
+       "      <td>0.756970</td>\n",
+       "      <td>0.140366</td>\n",
+       "      <td>0.329177</td>\n",
+       "      <td>0.308566</td>\n",
+       "      <td>0.646110</td>\n",
+       "      <td>0.866250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>0.447820</td>\n",
+       "      <td>0.321448</td>\n",
+       "      <td>0.258942</td>\n",
+       "      <td>0.363007</td>\n",
+       "      <td>0.812436</td>\n",
+       "      <td>0.153574</td>\n",
+       "      <td>0.317637</td>\n",
+       "      <td>0.274011</td>\n",
+       "      <td>0.699191</td>\n",
+       "      <td>0.869477</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>0.691779</td>\n",
+       "      <td>0.224665</td>\n",
+       "      <td>0.198090</td>\n",
+       "      <td>0.267166</td>\n",
+       "      <td>0.794502</td>\n",
+       "      <td>0.116110</td>\n",
+       "      <td>0.309170</td>\n",
+       "      <td>0.293167</td>\n",
+       "      <td>0.639747</td>\n",
+       "      <td>0.868581</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>0.685264</td>\n",
+       "      <td>0.350549</td>\n",
+       "      <td>0.139600</td>\n",
+       "      <td>0.392132</td>\n",
+       "      <td>0.767983</td>\n",
+       "      <td>0.136523</td>\n",
+       "      <td>0.298596</td>\n",
+       "      <td>0.303563</td>\n",
+       "      <td>0.754460</td>\n",
+       "      <td>0.883931</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>0.674900</td>\n",
+       "      <td>0.242929</td>\n",
+       "      <td>0.187755</td>\n",
+       "      <td>0.262379</td>\n",
+       "      <td>0.776482</td>\n",
+       "      <td>0.165717</td>\n",
+       "      <td>0.308648</td>\n",
+       "      <td>0.399038</td>\n",
+       "      <td>0.542904</td>\n",
+       "      <td>0.871608</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>0.683746</td>\n",
+       "      <td>0.276257</td>\n",
+       "      <td>0.131212</td>\n",
+       "      <td>0.232615</td>\n",
+       "      <td>0.744022</td>\n",
+       "      <td>0.109392</td>\n",
+       "      <td>0.270353</td>\n",
+       "      <td>0.460417</td>\n",
+       "      <td>0.564136</td>\n",
+       "      <td>0.865420</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>0.681126</td>\n",
+       "      <td>0.315604</td>\n",
+       "      <td>0.211662</td>\n",
+       "      <td>0.341304</td>\n",
+       "      <td>0.726985</td>\n",
+       "      <td>0.125056</td>\n",
+       "      <td>0.329450</td>\n",
+       "      <td>0.340761</td>\n",
+       "      <td>0.605783</td>\n",
+       "      <td>0.857388</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.736543</td>\n",
+       "      <td>0.333992</td>\n",
+       "      <td>0.214881</td>\n",
+       "      <td>0.374279</td>\n",
+       "      <td>0.744442</td>\n",
+       "      <td>0.153582</td>\n",
+       "      <td>0.362840</td>\n",
+       "      <td>0.229945</td>\n",
+       "      <td>0.664724</td>\n",
+       "      <td>0.853623</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>0.529423</td>\n",
+       "      <td>0.298333</td>\n",
+       "      <td>0.208892</td>\n",
+       "      <td>0.333575</td>\n",
+       "      <td>0.817312</td>\n",
+       "      <td>0.117149</td>\n",
+       "      <td>0.331304</td>\n",
+       "      <td>0.379668</td>\n",
+       "      <td>0.602769</td>\n",
+       "      <td>0.865487</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>0.663974</td>\n",
+       "      <td>0.327556</td>\n",
+       "      <td>0.153817</td>\n",
+       "      <td>0.364626</td>\n",
+       "      <td>0.733456</td>\n",
+       "      <td>0.101866</td>\n",
+       "      <td>0.272521</td>\n",
+       "      <td>0.216020</td>\n",
+       "      <td>0.624397</td>\n",
+       "      <td>0.841907</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0.750610</td>\n",
+       "      <td>0.354617</td>\n",
+       "      <td>0.220645</td>\n",
+       "      <td>0.382166</td>\n",
+       "      <td>0.738567</td>\n",
+       "      <td>0.153837</td>\n",
+       "      <td>0.295751</td>\n",
+       "      <td>0.159407</td>\n",
+       "      <td>0.743808</td>\n",
+       "      <td>0.851834</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>0.749898</td>\n",
+       "      <td>0.197995</td>\n",
+       "      <td>0.144894</td>\n",
+       "      <td>0.193128</td>\n",
+       "      <td>0.834317</td>\n",
+       "      <td>0.100931</td>\n",
+       "      <td>0.276633</td>\n",
+       "      <td>0.286145</td>\n",
+       "      <td>0.409425</td>\n",
+       "      <td>0.875360</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>55</th>\n",
+       "      <td>0.816347</td>\n",
+       "      <td>0.353310</td>\n",
+       "      <td>0.185828</td>\n",
+       "      <td>0.436315</td>\n",
+       "      <td>0.737862</td>\n",
+       "      <td>0.167934</td>\n",
+       "      <td>0.323200</td>\n",
+       "      <td>0.196694</td>\n",
+       "      <td>0.677641</td>\n",
+       "      <td>0.848497</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>0.714003</td>\n",
+       "      <td>0.297637</td>\n",
+       "      <td>0.186870</td>\n",
+       "      <td>0.369552</td>\n",
+       "      <td>0.766350</td>\n",
+       "      <td>0.115206</td>\n",
+       "      <td>0.335540</td>\n",
+       "      <td>0.303235</td>\n",
+       "      <td>0.663412</td>\n",
+       "      <td>0.877658</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>0.610422</td>\n",
+       "      <td>0.229268</td>\n",
+       "      <td>0.143579</td>\n",
+       "      <td>0.269061</td>\n",
+       "      <td>0.824474</td>\n",
+       "      <td>0.107828</td>\n",
+       "      <td>0.272571</td>\n",
+       "      <td>0.357828</td>\n",
+       "      <td>0.537741</td>\n",
+       "      <td>0.864665</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>63</th>\n",
+       "      <td>0.796604</td>\n",
+       "      <td>0.297169</td>\n",
+       "      <td>0.188544</td>\n",
+       "      <td>0.353510</td>\n",
+       "      <td>0.699362</td>\n",
+       "      <td>0.156235</td>\n",
+       "      <td>0.296926</td>\n",
+       "      <td>0.322834</td>\n",
+       "      <td>0.658940</td>\n",
+       "      <td>0.853995</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>0.744290</td>\n",
+       "      <td>0.383036</td>\n",
+       "      <td>0.270709</td>\n",
+       "      <td>0.412808</td>\n",
+       "      <td>0.739070</td>\n",
+       "      <td>0.168775</td>\n",
+       "      <td>0.331435</td>\n",
+       "      <td>0.156566</td>\n",
+       "      <td>0.690014</td>\n",
+       "      <td>0.848442</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>0.807414</td>\n",
+       "      <td>0.409579</td>\n",
+       "      <td>0.294675</td>\n",
+       "      <td>0.472013</td>\n",
+       "      <td>0.743354</td>\n",
+       "      <td>0.101803</td>\n",
+       "      <td>0.323678</td>\n",
+       "      <td>0.196633</td>\n",
+       "      <td>0.820077</td>\n",
+       "      <td>0.866920</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>0.675943</td>\n",
+       "      <td>0.284811</td>\n",
+       "      <td>0.198206</td>\n",
+       "      <td>0.249146</td>\n",
+       "      <td>0.805983</td>\n",
+       "      <td>0.139151</td>\n",
+       "      <td>0.278162</td>\n",
+       "      <td>0.337946</td>\n",
+       "      <td>0.628155</td>\n",
+       "      <td>0.856257</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>0.790656</td>\n",
+       "      <td>0.404174</td>\n",
+       "      <td>0.220056</td>\n",
+       "      <td>0.458372</td>\n",
+       "      <td>0.769968</td>\n",
+       "      <td>0.142000</td>\n",
+       "      <td>0.332258</td>\n",
+       "      <td>0.335693</td>\n",
+       "      <td>0.762892</td>\n",
+       "      <td>0.852804</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57</th>\n",
+       "      <td>0.755333</td>\n",
+       "      <td>0.375039</td>\n",
+       "      <td>0.161554</td>\n",
+       "      <td>0.432447</td>\n",
+       "      <td>0.739196</td>\n",
+       "      <td>0.127974</td>\n",
+       "      <td>0.303031</td>\n",
+       "      <td>0.226154</td>\n",
+       "      <td>0.672440</td>\n",
+       "      <td>0.860156</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>0.747794</td>\n",
+       "      <td>0.325598</td>\n",
+       "      <td>0.201969</td>\n",
+       "      <td>0.401492</td>\n",
+       "      <td>0.764157</td>\n",
+       "      <td>0.160552</td>\n",
+       "      <td>0.309608</td>\n",
+       "      <td>0.363677</td>\n",
+       "      <td>0.703451</td>\n",
+       "      <td>0.874326</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>0.679293</td>\n",
+       "      <td>0.457564</td>\n",
+       "      <td>0.252646</td>\n",
+       "      <td>0.580303</td>\n",
+       "      <td>0.639979</td>\n",
+       "      <td>0.143567</td>\n",
+       "      <td>0.419554</td>\n",
+       "      <td>0.309349</td>\n",
+       "      <td>0.871858</td>\n",
+       "      <td>0.829180</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Unnamed: 0  cg12440062  cg26106778  cg22746058  cg11775521  cg05724197  \\\n",
+       "51            0.735547    0.255999    0.162651    0.220624    0.746333   \n",
+       "25            0.813720    0.269805    0.134080    0.282190    0.789789   \n",
+       "1             0.678392    0.339627    0.240843    0.340537    0.756970   \n",
+       "9             0.447820    0.321448    0.258942    0.363007    0.812436   \n",
+       "33            0.691779    0.224665    0.198090    0.267166    0.794502   \n",
+       "11            0.685264    0.350549    0.139600    0.392132    0.767983   \n",
+       "27            0.674900    0.242929    0.187755    0.262379    0.776482   \n",
+       "23            0.683746    0.276257    0.131212    0.232615    0.744022   \n",
+       "47            0.681126    0.315604    0.211662    0.341304    0.726985   \n",
+       "3             0.736543    0.333992    0.214881    0.374279    0.744442   \n",
+       "5             0.529423    0.298333    0.208892    0.333575    0.817312   \n",
+       "53            0.663974    0.327556    0.153817    0.364626    0.733456   \n",
+       "7             0.750610    0.354617    0.220645    0.382166    0.738567   \n",
+       "43            0.749898    0.197995    0.144894    0.193128    0.834317   \n",
+       "55            0.816347    0.353310    0.185828    0.436315    0.737862   \n",
+       "45            0.714003    0.297637    0.186870    0.369552    0.766350   \n",
+       "37            0.610422    0.229268    0.143579    0.269061    0.824474   \n",
+       "63            0.796604    0.297169    0.188544    0.353510    0.699362   \n",
+       "41            0.744290    0.383036    0.270709    0.412808    0.739070   \n",
+       "15            0.807414    0.409579    0.294675    0.472013    0.743354   \n",
+       "21            0.675943    0.284811    0.198206    0.249146    0.805983   \n",
+       "29            0.790656    0.404174    0.220056    0.458372    0.769968   \n",
+       "57            0.755333    0.375039    0.161554    0.432447    0.739196   \n",
+       "39            0.747794    0.325598    0.201969    0.401492    0.764157   \n",
+       "13            0.679293    0.457564    0.252646    0.580303    0.639979   \n",
+       "\n",
+       "Unnamed: 0  cg05884032  cg04927004  cg07211259  cg04225088  cg23631930  \n",
+       "51            0.157506    0.291237    0.271578    0.426238    0.861214  \n",
+       "25            0.132311    0.311697    0.212900    0.477628    0.867339  \n",
+       "1             0.140366    0.329177    0.308566    0.646110    0.866250  \n",
+       "9             0.153574    0.317637    0.274011    0.699191    0.869477  \n",
+       "33            0.116110    0.309170    0.293167    0.639747    0.868581  \n",
+       "11            0.136523    0.298596    0.303563    0.754460    0.883931  \n",
+       "27            0.165717    0.308648    0.399038    0.542904    0.871608  \n",
+       "23            0.109392    0.270353    0.460417    0.564136    0.865420  \n",
+       "47            0.125056    0.329450    0.340761    0.605783    0.857388  \n",
+       "3             0.153582    0.362840    0.229945    0.664724    0.853623  \n",
+       "5             0.117149    0.331304    0.379668    0.602769    0.865487  \n",
+       "53            0.101866    0.272521    0.216020    0.624397    0.841907  \n",
+       "7             0.153837    0.295751    0.159407    0.743808    0.851834  \n",
+       "43            0.100931    0.276633    0.286145    0.409425    0.875360  \n",
+       "55            0.167934    0.323200    0.196694    0.677641    0.848497  \n",
+       "45            0.115206    0.335540    0.303235    0.663412    0.877658  \n",
+       "37            0.107828    0.272571    0.357828    0.537741    0.864665  \n",
+       "63            0.156235    0.296926    0.322834    0.658940    0.853995  \n",
+       "41            0.168775    0.331435    0.156566    0.690014    0.848442  \n",
+       "15            0.101803    0.323678    0.196633    0.820077    0.866920  \n",
+       "21            0.139151    0.278162    0.337946    0.628155    0.856257  \n",
+       "29            0.142000    0.332258    0.335693    0.762892    0.852804  \n",
+       "57            0.127974    0.303031    0.226154    0.672440    0.860156  \n",
+       "39            0.160552    0.309608    0.363677    0.703451    0.874326  \n",
+       "13            0.143567    0.419554    0.309349    0.871858    0.829180  "
+      ]
+     },
+     "execution_count": 132,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X = data_148663.T \n",
+    "y = y_test_148663\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
+    "def class_distribution(y):\n",
+    "    counts = np.bincount(y)\n",
+    "    labels = np.arange(len(counts))\n",
+    "    return pd.DataFrame({\n",
+    "        'Class': labels,\n",
+    "        'Count': counts,\n",
+    "        'Percentage': counts / len(y) * 100\n",
+    "    })\n",
+    "\n",
+    "# 訓練集類別分佈\n",
+    "train_dist = class_distribution(y_train)\n",
+    "print(\"訓練集類別分佈:\")\n",
+    "print(train_dist)\n",
+    "\n",
+    "# 測試集類別分佈\n",
+    "test_dist = class_distribution(y_test)\n",
+    "print(\"\\n測試集類別分佈:\")\n",
+    "print(test_dist)\n",
+    "\n",
+    "# 也可以顯示總數量\n",
+    "print(\"\\n訓練集和測試集的大小:\")\n",
+    "print(f\"訓練集大小: {len(X_train)}\")\n",
+    "print(f\"測試集大小: {len(X_test)}\")\n",
+    "X_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 133,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Model</th>\n",
+       "      <th>ID1</th>\n",
+       "      <th>ID2</th>\n",
+       "      <th>ID3</th>\n",
+       "      <th>ID4</th>\n",
+       "      <th>train_accuracy</th>\n",
+       "      <th>test_accuracy</th>\n",
+       "      <th>train - test accuracy</th>\n",
+       "      <th>AUC</th>\n",
+       "      <th>f1-score</th>\n",
+       "      <th>sensitivity</th>\n",
+       "      <th>specificity</th>\n",
+       "      <th>precision</th>\n",
+       "      <th>mcc</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Decision Tree</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>cg11775521</td>\n",
+       "      <td>cg04225088</td>\n",
+       "      <td>0.96</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.102857</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.730297</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Logistic Regression</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>cg11775521</td>\n",
+       "      <td>cg04225088</td>\n",
+       "      <td>0.72</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.280000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Random Forest</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>cg11775521</td>\n",
+       "      <td>cg04225088</td>\n",
+       "      <td>0.72</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.280000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>SVM</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>cg11775521</td>\n",
+       "      <td>cg04225088</td>\n",
+       "      <td>0.92</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.062857</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.909091</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.645497</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>XGBoost</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>cg11775521</td>\n",
+       "      <td>cg04225088</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>-0.057143</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.730297</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>115</th>\n",
+       "      <td>Decision Tree</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>cg07211259</td>\n",
+       "      <td>cg05884032</td>\n",
+       "      <td>0.84</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.160000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>116</th>\n",
+       "      <td>Logistic Regression</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>cg07211259</td>\n",
+       "      <td>cg05884032</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>-0.034286</td>\n",
+       "      <td>0.4</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>117</th>\n",
+       "      <td>Random Forest</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>cg07211259</td>\n",
+       "      <td>cg05884032</td>\n",
+       "      <td>0.88</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.165714</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>118</th>\n",
+       "      <td>SVM</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>cg07211259</td>\n",
+       "      <td>cg05884032</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>-0.034286</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>119</th>\n",
+       "      <td>XGBoost</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>cg07211259</td>\n",
+       "      <td>cg05884032</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.085714</td>\n",
+       "      <td>0.4</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>120 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   Model         ID1         ID2         ID3         ID4  \\\n",
+       "0          Decision Tree  cg04927004  cg23631930  cg11775521  cg04225088   \n",
+       "1    Logistic Regression  cg04927004  cg23631930  cg11775521  cg04225088   \n",
+       "2          Random Forest  cg04927004  cg23631930  cg11775521  cg04225088   \n",
+       "3                    SVM  cg04927004  cg23631930  cg11775521  cg04225088   \n",
+       "4                XGBoost  cg04927004  cg23631930  cg11775521  cg04225088   \n",
+       "..                   ...         ...         ...         ...         ...   \n",
+       "115        Decision Tree  cg04927004  cg05724197  cg07211259  cg05884032   \n",
+       "116  Logistic Regression  cg04927004  cg05724197  cg07211259  cg05884032   \n",
+       "117        Random Forest  cg04927004  cg05724197  cg07211259  cg05884032   \n",
+       "118                  SVM  cg04927004  cg05724197  cg07211259  cg05884032   \n",
+       "119              XGBoost  cg04927004  cg05724197  cg07211259  cg05884032   \n",
+       "\n",
+       "     train_accuracy  test_accuracy  train - test accuracy  AUC  f1-score  \\\n",
+       "0              0.96       0.857143               0.102857  0.9  0.888889   \n",
+       "1              0.72       1.000000              -0.280000  1.0  1.000000   \n",
+       "2              0.72       1.000000              -0.280000  1.0  1.000000   \n",
+       "3              0.92       0.857143               0.062857  1.0  0.909091   \n",
+       "4              0.80       0.857143              -0.057143  0.9  0.888889   \n",
+       "..              ...            ...                    ...  ...       ...   \n",
+       "115            0.84       1.000000              -0.160000  1.0  1.000000   \n",
+       "116            0.68       0.714286              -0.034286  0.4  0.833333   \n",
+       "117            0.88       0.714286               0.165714  1.0  0.833333   \n",
+       "118            0.68       0.714286              -0.034286  0.0  0.833333   \n",
+       "119            0.80       0.714286               0.085714  0.4  0.833333   \n",
+       "\n",
+       "     sensitivity  specificity  precision       mcc  \n",
+       "0            0.8          1.0   1.000000  0.730297  \n",
+       "1            1.0          1.0   1.000000  1.000000  \n",
+       "2            1.0          1.0   1.000000  1.000000  \n",
+       "3            1.0          0.5   0.833333  0.645497  \n",
+       "4            0.8          1.0   1.000000  0.730297  \n",
+       "..           ...          ...        ...       ...  \n",
+       "115          1.0          1.0   1.000000  1.000000  \n",
+       "116          1.0          0.0   0.714286  0.000000  \n",
+       "117          1.0          0.0   0.714286  0.000000  \n",
+       "118          1.0          0.0   0.714286  0.000000  \n",
+       "119          1.0          0.0   0.714286  0.000000  \n",
+       "\n",
+       "[120 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 133,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "from sklearn.svm import SVC\n",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "import xgboost as xgb\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.metrics import classification_report, roc_auc_score, accuracy_score, precision_score, recall_score, f1_score\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from xgboost import XGBClassifier\n",
+    "from sklearn.model_selection import RandomizedSearchCV\n",
+    "from sklearn.model_selection import GridSearchCV\n",
+    "from skopt import BayesSearchCV\n",
+    "from skopt.space import Categorical, Real\n",
+    "from sklearn.metrics import (\n",
+    "    confusion_matrix,\n",
+    "    precision_score,\n",
+    "    accuracy_score,\n",
+    "    matthews_corrcoef,\n",
+    "    f1_score,\n",
+    ")\n",
+    "\n",
+    "\n",
+    "tree_params = {\"max_depth\": [3, 5, 7], \"min_samples_split\": [2, 5, 10]}\n",
+    "\n",
+    "clf_tree = DecisionTreeClassifier()\n",
+    "\n",
+    "lr_params = [\n",
+    "   {\"C\": [0.001,0.01,0.1, 1, 10], \"solver\": [\"liblinear\"]}\n",
+    "]\n",
+    "\n",
+    "clf_lr = LogisticRegression(max_iter=500) \n",
+    "\n",
+    "\n",
+    "rf_params = {\n",
+    "        \"n_estimators\": [100,150, 200],\n",
+    "        \"max_depth\": [1,3, 5, 7],\n",
+    "        \"min_samples_split\": [2, 5, 10],\n",
+    "    }\n",
+    "clf_rf = RandomForestClassifier()\n",
+    "\n",
+    "svm_params = {\"C\": [0.001,0.1, 1, 10,100,1000], \"kernel\": [\"linear\", \"rbf\"]}\n",
+    "\n",
+    "clf_svm = SVC(probability=True)\n",
+    "\n",
+    "\n",
+    "xgb_params = {\n",
+    "        \"n_estimators\": [100,150, 200],\n",
+    "        \"max_depth\": [3, 5, 7],\n",
+    "        \"learning_rate\": [0.01, 0.1, 0.2],\n",
+    "    }\n",
+    "\n",
+    "clf_xgb = XGBClassifier( eval_metric='logloss')\n",
+    "\n",
+    "results = []\n",
+    "\n",
+    "model_list = [clf_tree,clf_lr,clf_rf,clf_svm,clf_xgb]\n",
+    "model_param = [tree_params,lr_params,rf_params,svm_params,xgb_params]\n",
+    "model_names = ['Decision Tree', 'Logistic Regression', 'Random Forest', 'SVM', 'XGBoost']\n",
+    "\n",
+    "for cg in cg_list:\n",
+    "    X_train_c = X_train[cg]\n",
+    "    X_test_c = X_test[cg]\n",
+    "    \n",
+    "    for model,param, model_name in zip(model_list,model_param, model_names):\n",
+    "        \n",
+    "        model = GridSearchCV(\n",
+    "                    estimator=model, param_grid=param, cv=5, n_jobs=-1\n",
+    "        )\n",
+    "        model.fit(X_train_c, y_train)\n",
+    "        \n",
+    "        y_pred = model.predict(X_test_c)\n",
+    "        y_pred_prob = model.predict_proba(X_test_c)[:, 1]\n",
+    "        \n",
+    "        y_pred_train = model.predict(X_train_c)\n",
+    "        y_pred_prob_train = model.predict_proba(X_train_c)[:, 1]\n",
+    "        # report = classification_report(y_test, y_pred, output_dict=True)\n",
+    "        auc = roc_auc_score(y_test, y_pred_prob)\n",
+    "        \n",
+    "        train_accuracy = accuracy_score(y_train, y_pred_train)\n",
+    "        test_accuracy = accuracy_score(y_test, y_pred)\n",
+    "        precision = precision_score(y_test, y_pred,zero_division=0)\n",
+    "        sensitivity = recall_score(y_test, y_pred)\n",
+    "        specificity = recall_score(y_test, y_pred, pos_label=0)\n",
+    "        f1 = f1_score(y_test, y_pred)\n",
+    "        mcc = matthews_corrcoef(y_test, y_pred)\n",
+    "\n",
+    "\n",
+    "        # 計算複合指標\\\n",
+    "        \n",
+    "        results.append( {\n",
+    "            'Model': model_name,\n",
+    "            'ID1': cg[0],\n",
+    "            'ID2': cg[1],\n",
+    "            'ID3': cg[2],\n",
+    "            'ID4': cg[3],\n",
+    "            'train_accuracy': train_accuracy,\n",
+    "            'test_accuracy': test_accuracy,\n",
+    "            'train - test accuracy' : train_accuracy - test_accuracy,\n",
+    "            'AUC': auc,\n",
+    "            'f1-score': f1,\n",
+    "            'sensitivity': sensitivity,\n",
+    "            'specificity': specificity,\n",
+    "            'precision': precision,\n",
+    "            'mcc' : mcc\n",
+    "        })\n",
+    "df = pd.DataFrame(results)\n",
+    "\n",
+    "df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 134,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "df.to_csv(\"result/test_aba2/5_fold_148663_hyper.csv\",index=False)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/breast/ml/ics_aba/ml_RFE_BORUTA.ipynb b/breast/ml/ics_aba/ml_RFE_BORUTA.ipynb
new file mode 100644
index 0000000..12b488e
--- /dev/null
+++ b/breast/ml/ics_aba/ml_RFE_BORUTA.ipynb
@@ -0,0 +1,6274 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Bouta + RFECV 進行特徵選擇"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>...</th>\n",
+       "      <th>408</th>\n",
+       "      <th>409</th>\n",
+       "      <th>410</th>\n",
+       "      <th>411</th>\n",
+       "      <th>412</th>\n",
+       "      <th>413</th>\n",
+       "      <th>414</th>\n",
+       "      <th>415</th>\n",
+       "      <th>416</th>\n",
+       "      <th>417</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg07881041</td>\n",
+       "      <td>0.926368</td>\n",
+       "      <td>0.940674</td>\n",
+       "      <td>0.946855</td>\n",
+       "      <td>0.939445</td>\n",
+       "      <td>0.939303</td>\n",
+       "      <td>0.940384</td>\n",
+       "      <td>0.956939</td>\n",
+       "      <td>0.940137</td>\n",
+       "      <td>0.929561</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.942149</td>\n",
+       "      <td>0.935299</td>\n",
+       "      <td>0.952236</td>\n",
+       "      <td>0.907088</td>\n",
+       "      <td>0.948924</td>\n",
+       "      <td>0.953512</td>\n",
+       "      <td>0.931727</td>\n",
+       "      <td>0.949121</td>\n",
+       "      <td>0.932493</td>\n",
+       "      <td>0.940154</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg03513874</td>\n",
+       "      <td>0.950997</td>\n",
+       "      <td>0.971682</td>\n",
+       "      <td>0.962746</td>\n",
+       "      <td>0.942406</td>\n",
+       "      <td>0.943713</td>\n",
+       "      <td>0.967288</td>\n",
+       "      <td>0.961146</td>\n",
+       "      <td>0.959091</td>\n",
+       "      <td>0.958049</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.932625</td>\n",
+       "      <td>0.964292</td>\n",
+       "      <td>0.952845</td>\n",
+       "      <td>0.946885</td>\n",
+       "      <td>0.940200</td>\n",
+       "      <td>0.940072</td>\n",
+       "      <td>0.956672</td>\n",
+       "      <td>0.955850</td>\n",
+       "      <td>0.947340</td>\n",
+       "      <td>0.951423</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg05451842</td>\n",
+       "      <td>0.059963</td>\n",
+       "      <td>0.019628</td>\n",
+       "      <td>0.017954</td>\n",
+       "      <td>0.025166</td>\n",
+       "      <td>0.039009</td>\n",
+       "      <td>0.022807</td>\n",
+       "      <td>0.043550</td>\n",
+       "      <td>0.041088</td>\n",
+       "      <td>0.030474</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.018186</td>\n",
+       "      <td>0.022440</td>\n",
+       "      <td>0.048736</td>\n",
+       "      <td>0.033335</td>\n",
+       "      <td>0.028952</td>\n",
+       "      <td>0.039987</td>\n",
+       "      <td>0.038657</td>\n",
+       "      <td>0.024731</td>\n",
+       "      <td>0.036287</td>\n",
+       "      <td>0.039251</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg14797042</td>\n",
+       "      <td>0.951165</td>\n",
+       "      <td>0.983220</td>\n",
+       "      <td>0.972501</td>\n",
+       "      <td>0.971123</td>\n",
+       "      <td>0.983623</td>\n",
+       "      <td>0.978537</td>\n",
+       "      <td>0.969215</td>\n",
+       "      <td>0.978323</td>\n",
+       "      <td>0.971569</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.975007</td>\n",
+       "      <td>0.973183</td>\n",
+       "      <td>0.972620</td>\n",
+       "      <td>0.974413</td>\n",
+       "      <td>0.969948</td>\n",
+       "      <td>0.979849</td>\n",
+       "      <td>0.952180</td>\n",
+       "      <td>0.982432</td>\n",
+       "      <td>0.975147</td>\n",
+       "      <td>0.963315</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg09838562</td>\n",
+       "      <td>0.038691</td>\n",
+       "      <td>0.010217</td>\n",
+       "      <td>0.018484</td>\n",
+       "      <td>0.023737</td>\n",
+       "      <td>0.023379</td>\n",
+       "      <td>0.014493</td>\n",
+       "      <td>0.013606</td>\n",
+       "      <td>0.024030</td>\n",
+       "      <td>0.028147</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.016635</td>\n",
+       "      <td>0.022670</td>\n",
+       "      <td>0.022354</td>\n",
+       "      <td>0.033122</td>\n",
+       "      <td>0.010799</td>\n",
+       "      <td>0.018510</td>\n",
+       "      <td>0.018724</td>\n",
+       "      <td>0.010245</td>\n",
+       "      <td>0.016267</td>\n",
+       "      <td>0.043327</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730295</th>\n",
+       "      <td>cg06272054</td>\n",
+       "      <td>0.029346</td>\n",
+       "      <td>0.006511</td>\n",
+       "      <td>0.014298</td>\n",
+       "      <td>0.007345</td>\n",
+       "      <td>0.022802</td>\n",
+       "      <td>0.013567</td>\n",
+       "      <td>0.028430</td>\n",
+       "      <td>0.018687</td>\n",
+       "      <td>0.026299</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.017863</td>\n",
+       "      <td>0.013923</td>\n",
+       "      <td>0.028921</td>\n",
+       "      <td>0.016757</td>\n",
+       "      <td>0.013196</td>\n",
+       "      <td>0.019271</td>\n",
+       "      <td>0.018279</td>\n",
+       "      <td>0.017410</td>\n",
+       "      <td>0.008597</td>\n",
+       "      <td>0.018308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730296</th>\n",
+       "      <td>cg07255356</td>\n",
+       "      <td>0.040948</td>\n",
+       "      <td>0.021189</td>\n",
+       "      <td>0.029187</td>\n",
+       "      <td>0.013176</td>\n",
+       "      <td>0.029784</td>\n",
+       "      <td>0.021071</td>\n",
+       "      <td>0.028229</td>\n",
+       "      <td>0.029944</td>\n",
+       "      <td>0.034253</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.022560</td>\n",
+       "      <td>0.024299</td>\n",
+       "      <td>0.045046</td>\n",
+       "      <td>0.026598</td>\n",
+       "      <td>0.021732</td>\n",
+       "      <td>0.030806</td>\n",
+       "      <td>0.028840</td>\n",
+       "      <td>0.020497</td>\n",
+       "      <td>0.025104</td>\n",
+       "      <td>0.029068</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730297</th>\n",
+       "      <td>cg24220897</td>\n",
+       "      <td>0.909573</td>\n",
+       "      <td>0.950804</td>\n",
+       "      <td>0.953917</td>\n",
+       "      <td>0.930564</td>\n",
+       "      <td>0.909081</td>\n",
+       "      <td>0.933142</td>\n",
+       "      <td>0.955900</td>\n",
+       "      <td>0.927729</td>\n",
+       "      <td>0.916943</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.895366</td>\n",
+       "      <td>0.941694</td>\n",
+       "      <td>0.916555</td>\n",
+       "      <td>0.944813</td>\n",
+       "      <td>0.934123</td>\n",
+       "      <td>0.885239</td>\n",
+       "      <td>0.926268</td>\n",
+       "      <td>0.899603</td>\n",
+       "      <td>0.934250</td>\n",
+       "      <td>0.910259</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730298</th>\n",
+       "      <td>cg12325588</td>\n",
+       "      <td>0.046572</td>\n",
+       "      <td>0.007867</td>\n",
+       "      <td>0.024592</td>\n",
+       "      <td>0.017405</td>\n",
+       "      <td>0.028294</td>\n",
+       "      <td>0.013181</td>\n",
+       "      <td>0.016499</td>\n",
+       "      <td>0.019857</td>\n",
+       "      <td>0.014280</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.018293</td>\n",
+       "      <td>0.030286</td>\n",
+       "      <td>0.017973</td>\n",
+       "      <td>0.033730</td>\n",
+       "      <td>0.015526</td>\n",
+       "      <td>0.029521</td>\n",
+       "      <td>0.020975</td>\n",
+       "      <td>0.013991</td>\n",
+       "      <td>0.021318</td>\n",
+       "      <td>0.019140</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730299</th>\n",
+       "      <td>label</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>730300 rows × 419 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unnamed: 0         0         1         2         3         4  \\\n",
+       "0       cg07881041  0.926368  0.940674  0.946855  0.939445  0.939303   \n",
+       "1       cg03513874  0.950997  0.971682  0.962746  0.942406  0.943713   \n",
+       "2       cg05451842  0.059963  0.019628  0.017954  0.025166  0.039009   \n",
+       "3       cg14797042  0.951165  0.983220  0.972501  0.971123  0.983623   \n",
+       "4       cg09838562  0.038691  0.010217  0.018484  0.023737  0.023379   \n",
+       "...            ...       ...       ...       ...       ...       ...   \n",
+       "730295  cg06272054  0.029346  0.006511  0.014298  0.007345  0.022802   \n",
+       "730296  cg07255356  0.040948  0.021189  0.029187  0.013176  0.029784   \n",
+       "730297  cg24220897  0.909573  0.950804  0.953917  0.930564  0.909081   \n",
+       "730298  cg12325588  0.046572  0.007867  0.024592  0.017405  0.028294   \n",
+       "730299       label  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "\n",
+       "               5         6         7         8  ...       408       409  \\\n",
+       "0       0.940384  0.956939  0.940137  0.929561  ...  0.942149  0.935299   \n",
+       "1       0.967288  0.961146  0.959091  0.958049  ...  0.932625  0.964292   \n",
+       "2       0.022807  0.043550  0.041088  0.030474  ...  0.018186  0.022440   \n",
+       "3       0.978537  0.969215  0.978323  0.971569  ...  0.975007  0.973183   \n",
+       "4       0.014493  0.013606  0.024030  0.028147  ...  0.016635  0.022670   \n",
+       "...          ...       ...       ...       ...  ...       ...       ...   \n",
+       "730295  0.013567  0.028430  0.018687  0.026299  ...  0.017863  0.013923   \n",
+       "730296  0.021071  0.028229  0.029944  0.034253  ...  0.022560  0.024299   \n",
+       "730297  0.933142  0.955900  0.927729  0.916943  ...  0.895366  0.941694   \n",
+       "730298  0.013181  0.016499  0.019857  0.014280  ...  0.018293  0.030286   \n",
+       "730299  0.000000  0.000000  0.000000  0.000000  ...  1.000000  1.000000   \n",
+       "\n",
+       "             410       411       412       413       414       415       416  \\\n",
+       "0       0.952236  0.907088  0.948924  0.953512  0.931727  0.949121  0.932493   \n",
+       "1       0.952845  0.946885  0.940200  0.940072  0.956672  0.955850  0.947340   \n",
+       "2       0.048736  0.033335  0.028952  0.039987  0.038657  0.024731  0.036287   \n",
+       "3       0.972620  0.974413  0.969948  0.979849  0.952180  0.982432  0.975147   \n",
+       "4       0.022354  0.033122  0.010799  0.018510  0.018724  0.010245  0.016267   \n",
+       "...          ...       ...       ...       ...       ...       ...       ...   \n",
+       "730295  0.028921  0.016757  0.013196  0.019271  0.018279  0.017410  0.008597   \n",
+       "730296  0.045046  0.026598  0.021732  0.030806  0.028840  0.020497  0.025104   \n",
+       "730297  0.916555  0.944813  0.934123  0.885239  0.926268  0.899603  0.934250   \n",
+       "730298  0.017973  0.033730  0.015526  0.029521  0.020975  0.013991  0.021318   \n",
+       "730299  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000   \n",
+       "\n",
+       "             417  \n",
+       "0       0.940154  \n",
+       "1       0.951423  \n",
+       "2       0.039251  \n",
+       "3       0.963315  \n",
+       "4       0.043327  \n",
+       "...          ...  \n",
+       "730295  0.018308  \n",
+       "730296  0.029068  \n",
+       "730297  0.910259  \n",
+       "730298  0.019140  \n",
+       "730299  1.000000  \n",
+       "\n",
+       "[730300 rows x 419 columns]"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd \n",
+    "import numpy as np\n",
+    "\n",
+    "df_beta_train = pd.read_csv(\"result/GSE243529_xzh/all_beta_normalized_train.csv\")\n",
+    "df_beta_train\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ID</th>\n",
+       "      <th>gene</th>\n",
+       "      <th>dbeta</th>\n",
+       "      <th>feature</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg03760483</td>\n",
+       "      <td>ALOX12</td>\n",
+       "      <td>0.157175</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg00074348</td>\n",
+       "      <td>APLNR</td>\n",
+       "      <td>-0.187434</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg04290171</td>\n",
+       "      <td>CD46</td>\n",
+       "      <td>-0.201098</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg00044665</td>\n",
+       "      <td>CDH5</td>\n",
+       "      <td>0.206568</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg14666310</td>\n",
+       "      <td>CEACAM5</td>\n",
+       "      <td>-0.210341</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>cg07157107</td>\n",
+       "      <td>CHRNA6</td>\n",
+       "      <td>-0.242190</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>cg02295216</td>\n",
+       "      <td>CKLF</td>\n",
+       "      <td>0.172590</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>cg19223467</td>\n",
+       "      <td>CLEC9A</td>\n",
+       "      <td>-0.152339</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>CMTM5</td>\n",
+       "      <td>0.172075</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>cg12440062</td>\n",
+       "      <td>CRISP2</td>\n",
+       "      <td>0.200273</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>cg21290814</td>\n",
+       "      <td>CRTC1</td>\n",
+       "      <td>-0.160943</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>cg01136458</td>\n",
+       "      <td>CSMD1</td>\n",
+       "      <td>-0.183525</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>CX3CL1</td>\n",
+       "      <td>0.198136</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>cg03003745</td>\n",
+       "      <td>CXCL17</td>\n",
+       "      <td>-0.238256</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>cg00213123</td>\n",
+       "      <td>CYP1A1</td>\n",
+       "      <td>0.195047</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>cg20051772</td>\n",
+       "      <td>DGKA</td>\n",
+       "      <td>-0.186669</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>cg13379236</td>\n",
+       "      <td>EGF</td>\n",
+       "      <td>-0.151026</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>cg13816423</td>\n",
+       "      <td>FOXP4</td>\n",
+       "      <td>-0.206186</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>cg07014349</td>\n",
+       "      <td>GJB5</td>\n",
+       "      <td>0.162041</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>cg19772011</td>\n",
+       "      <td>GLP1R</td>\n",
+       "      <td>-0.174030</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>cg17413194</td>\n",
+       "      <td>GNA13</td>\n",
+       "      <td>0.174816</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>cg04225088</td>\n",
+       "      <td>HIPK3</td>\n",
+       "      <td>0.150001</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>cg05818394</td>\n",
+       "      <td>HMGB1</td>\n",
+       "      <td>-0.291705</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>cg00727675</td>\n",
+       "      <td>HOXA3</td>\n",
+       "      <td>-0.182567</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>cg00239353</td>\n",
+       "      <td>IL32</td>\n",
+       "      <td>0.230341</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>cg15059851</td>\n",
+       "      <td>IVL</td>\n",
+       "      <td>-0.208371</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>cg11775521</td>\n",
+       "      <td>KCNE3</td>\n",
+       "      <td>0.263576</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>cg08375658</td>\n",
+       "      <td>KLK12</td>\n",
+       "      <td>-0.150620</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>cg07925549</td>\n",
+       "      <td>KRT75</td>\n",
+       "      <td>-0.170578</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>cg24296478</td>\n",
+       "      <td>LCOR</td>\n",
+       "      <td>-0.157586</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>cg23792592</td>\n",
+       "      <td>MIR1-1</td>\n",
+       "      <td>-0.180821</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>cg19157647</td>\n",
+       "      <td>MIR1180</td>\n",
+       "      <td>0.157648</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>cg11201447</td>\n",
+       "      <td>MIR1204</td>\n",
+       "      <td>-0.298594</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>MIR124-3</td>\n",
+       "      <td>0.177844</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>cg10734581</td>\n",
+       "      <td>MIR134</td>\n",
+       "      <td>-0.266630</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>cg24702147</td>\n",
+       "      <td>MIR141</td>\n",
+       "      <td>-0.157450</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>cg16570507</td>\n",
+       "      <td>MIR346</td>\n",
+       "      <td>-0.179525</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>cg02577745</td>\n",
+       "      <td>MIR493</td>\n",
+       "      <td>-0.163426</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>cg22500132</td>\n",
+       "      <td>MUC1</td>\n",
+       "      <td>-0.282771</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>cg21298408</td>\n",
+       "      <td>NAT1</td>\n",
+       "      <td>-0.159201</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>cg07552803</td>\n",
+       "      <td>NEFM</td>\n",
+       "      <td>0.227250</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>cg08317412</td>\n",
+       "      <td>PANX3</td>\n",
+       "      <td>-0.169833</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>cg20248866</td>\n",
+       "      <td>PCYT2</td>\n",
+       "      <td>0.154787</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>cg07211259</td>\n",
+       "      <td>PDCD1LG2</td>\n",
+       "      <td>0.152846</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>cg12871376</td>\n",
+       "      <td>PGC</td>\n",
+       "      <td>-0.152930</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>cg02329916</td>\n",
+       "      <td>PRSS1</td>\n",
+       "      <td>-0.206755</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>cg22746058</td>\n",
+       "      <td>PTF1A</td>\n",
+       "      <td>0.189984</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>cg05506480</td>\n",
+       "      <td>RAB6B</td>\n",
+       "      <td>-0.195065</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>cg26106778</td>\n",
+       "      <td>RING1</td>\n",
+       "      <td>0.186264</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>cg05884032</td>\n",
+       "      <td>SALL3</td>\n",
+       "      <td>0.151857</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>cg20596724</td>\n",
+       "      <td>SDR9C7</td>\n",
+       "      <td>-0.198220</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>cg16536739</td>\n",
+       "      <td>SFRP5</td>\n",
+       "      <td>-0.152947</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>cg04433322</td>\n",
+       "      <td>SLC4A1</td>\n",
+       "      <td>-0.211638</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>cg02547394</td>\n",
+       "      <td>SOX1</td>\n",
+       "      <td>0.228038</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>54</th>\n",
+       "      <td>cg12610471</td>\n",
+       "      <td>SPAG6</td>\n",
+       "      <td>0.281363</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>55</th>\n",
+       "      <td>cg06314202</td>\n",
+       "      <td>SSTR5</td>\n",
+       "      <td>-0.208831</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56</th>\n",
+       "      <td>cg06447795</td>\n",
+       "      <td>TGM2</td>\n",
+       "      <td>-0.193115</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57</th>\n",
+       "      <td>cg14153654</td>\n",
+       "      <td>TNFRSF9</td>\n",
+       "      <td>-0.195903</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58</th>\n",
+       "      <td>cg24073122</td>\n",
+       "      <td>TP73</td>\n",
+       "      <td>0.209996</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>59</th>\n",
+       "      <td>cg23571857</td>\n",
+       "      <td>XAF1</td>\n",
+       "      <td>0.216849</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            ID      gene     dbeta  feature\n",
+       "0   cg03760483    ALOX12  0.157175   TSS200\n",
+       "1   cg00074348     APLNR -0.187434  TSS1500\n",
+       "2   cg04290171      CD46 -0.201098  TSS1500\n",
+       "3   cg00044665      CDH5  0.206568   TSS200\n",
+       "4   cg14666310   CEACAM5 -0.210341  TSS1500\n",
+       "5   cg07157107    CHRNA6 -0.242190   TSS200\n",
+       "6   cg02295216      CKLF  0.172590  TSS1500\n",
+       "7   cg19223467    CLEC9A -0.152339   TSS200\n",
+       "8   cg23631930     CMTM5  0.172075   TSS200\n",
+       "9   cg12440062    CRISP2  0.200273   TSS200\n",
+       "10  cg21290814     CRTC1 -0.160943  TSS1500\n",
+       "11  cg01136458     CSMD1 -0.183525  TSS1500\n",
+       "12  cg05724197    CX3CL1  0.198136  TSS1500\n",
+       "13  cg03003745    CXCL17 -0.238256  TSS1500\n",
+       "14  cg00213123    CYP1A1  0.195047  TSS1500\n",
+       "15  cg20051772      DGKA -0.186669  TSS1500\n",
+       "16  cg13379236       EGF -0.151026  TSS1500\n",
+       "17  cg13816423     FOXP4 -0.206186  TSS1500\n",
+       "18  cg07014349      GJB5  0.162041   TSS200\n",
+       "19  cg19772011     GLP1R -0.174030  TSS1500\n",
+       "20  cg17413194     GNA13  0.174816  TSS1500\n",
+       "21  cg04225088     HIPK3  0.150001  TSS1500\n",
+       "22  cg05818394     HMGB1 -0.291705  TSS1500\n",
+       "23  cg00727675     HOXA3 -0.182567  TSS1500\n",
+       "24  cg00239353      IL32  0.230341  TSS1500\n",
+       "25  cg15059851       IVL -0.208371  TSS1500\n",
+       "26  cg11775521     KCNE3  0.263576   TSS200\n",
+       "27  cg08375658     KLK12 -0.150620  TSS1500\n",
+       "28  cg07925549     KRT75 -0.170578  TSS1500\n",
+       "29  cg24296478      LCOR -0.157586  TSS1500\n",
+       "30  cg23792592    MIR1-1 -0.180821  TSS1500\n",
+       "31  cg19157647   MIR1180  0.157648   TSS200\n",
+       "32  cg11201447   MIR1204 -0.298594   TSS200\n",
+       "33  cg04927004  MIR124-3  0.177844  TSS1500\n",
+       "34  cg10734581    MIR134 -0.266630  TSS1500\n",
+       "35  cg24702147    MIR141 -0.157450  TSS1500\n",
+       "36  cg16570507    MIR346 -0.179525   TSS200\n",
+       "37  cg02577745    MIR493 -0.163426  TSS1500\n",
+       "38  cg22500132      MUC1 -0.282771   TSS200\n",
+       "39  cg21298408      NAT1 -0.159201   TSS200\n",
+       "40  cg07552803      NEFM  0.227250  TSS1500\n",
+       "41  cg08317412     PANX3 -0.169833  TSS1500\n",
+       "42  cg20248866     PCYT2  0.154787  TSS1500\n",
+       "43  cg07211259  PDCD1LG2  0.152846   TSS200\n",
+       "44  cg12871376       PGC -0.152930  TSS1500\n",
+       "45  cg02329916     PRSS1 -0.206755   TSS200\n",
+       "46  cg22746058     PTF1A  0.189984  TSS1500\n",
+       "47  cg05506480     RAB6B -0.195065  TSS1500\n",
+       "48  cg26106778     RING1  0.186264  TSS1500\n",
+       "49  cg05884032     SALL3  0.151857   TSS200\n",
+       "50  cg20596724    SDR9C7 -0.198220  TSS1500\n",
+       "51  cg16536739     SFRP5 -0.152947  TSS1500\n",
+       "52  cg04433322    SLC4A1 -0.211638  TSS1500\n",
+       "53  cg02547394      SOX1  0.228038   TSS200\n",
+       "54  cg12610471     SPAG6  0.281363   TSS200\n",
+       "55  cg06314202     SSTR5 -0.208831  TSS1500\n",
+       "56  cg06447795      TGM2 -0.193115  TSS1500\n",
+       "57  cg14153654   TNFRSF9 -0.195903   TSS200\n",
+       "58  cg24073122      TP73  0.209996  TSS1500\n",
+       "59  cg23571857      XAF1  0.216849  TSS1500"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_dbeta = pd.read_csv(\"result/GSE243529_xzh/dbeta_GSE243529_TSS_0.15.csv\")\n",
+    "# result_max_per_gene_single_GSE243529_filter001_hyper_TSS\n",
+    "df_dbeta"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ID</th>\n",
+       "      <th>gene</th>\n",
+       "      <th>dbeta</th>\n",
+       "      <th>feature</th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>...</th>\n",
+       "      <th>408</th>\n",
+       "      <th>409</th>\n",
+       "      <th>410</th>\n",
+       "      <th>411</th>\n",
+       "      <th>412</th>\n",
+       "      <th>413</th>\n",
+       "      <th>414</th>\n",
+       "      <th>415</th>\n",
+       "      <th>416</th>\n",
+       "      <th>417</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg03760483</td>\n",
+       "      <td>ALOX12</td>\n",
+       "      <td>0.157175</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg03760483</td>\n",
+       "      <td>0.236414</td>\n",
+       "      <td>0.456963</td>\n",
+       "      <td>0.393205</td>\n",
+       "      <td>0.319442</td>\n",
+       "      <td>0.376546</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.433266</td>\n",
+       "      <td>0.385754</td>\n",
+       "      <td>0.365361</td>\n",
+       "      <td>0.571618</td>\n",
+       "      <td>0.389705</td>\n",
+       "      <td>0.376265</td>\n",
+       "      <td>0.200213</td>\n",
+       "      <td>0.213818</td>\n",
+       "      <td>0.223605</td>\n",
+       "      <td>0.390453</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg00074348</td>\n",
+       "      <td>APLNR</td>\n",
+       "      <td>-0.187434</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg00074348</td>\n",
+       "      <td>0.466309</td>\n",
+       "      <td>0.457003</td>\n",
+       "      <td>0.442229</td>\n",
+       "      <td>0.460896</td>\n",
+       "      <td>0.526294</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.406462</td>\n",
+       "      <td>0.468974</td>\n",
+       "      <td>0.505998</td>\n",
+       "      <td>0.447733</td>\n",
+       "      <td>0.496243</td>\n",
+       "      <td>0.516885</td>\n",
+       "      <td>0.478009</td>\n",
+       "      <td>0.461991</td>\n",
+       "      <td>0.505650</td>\n",
+       "      <td>0.425387</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg04290171</td>\n",
+       "      <td>CD46</td>\n",
+       "      <td>-0.201098</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg04290171</td>\n",
+       "      <td>0.889514</td>\n",
+       "      <td>0.860040</td>\n",
+       "      <td>0.825669</td>\n",
+       "      <td>0.808767</td>\n",
+       "      <td>0.882251</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.897428</td>\n",
+       "      <td>0.842283</td>\n",
+       "      <td>0.886778</td>\n",
+       "      <td>0.903050</td>\n",
+       "      <td>0.897832</td>\n",
+       "      <td>0.819984</td>\n",
+       "      <td>0.803872</td>\n",
+       "      <td>0.918829</td>\n",
+       "      <td>0.854414</td>\n",
+       "      <td>0.911942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg00044665</td>\n",
+       "      <td>CDH5</td>\n",
+       "      <td>0.206568</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg00044665</td>\n",
+       "      <td>0.266689</td>\n",
+       "      <td>0.332246</td>\n",
+       "      <td>0.269771</td>\n",
+       "      <td>0.315645</td>\n",
+       "      <td>0.234602</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.274103</td>\n",
+       "      <td>0.259853</td>\n",
+       "      <td>0.229335</td>\n",
+       "      <td>0.328268</td>\n",
+       "      <td>0.299035</td>\n",
+       "      <td>0.222106</td>\n",
+       "      <td>0.224438</td>\n",
+       "      <td>0.277983</td>\n",
+       "      <td>0.251191</td>\n",
+       "      <td>0.253250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg14666310</td>\n",
+       "      <td>CEACAM5</td>\n",
+       "      <td>-0.210341</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg14666310</td>\n",
+       "      <td>0.673555</td>\n",
+       "      <td>0.695180</td>\n",
+       "      <td>0.686634</td>\n",
+       "      <td>0.641230</td>\n",
+       "      <td>0.743104</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.681935</td>\n",
+       "      <td>0.613599</td>\n",
+       "      <td>0.728985</td>\n",
+       "      <td>0.664602</td>\n",
+       "      <td>0.685677</td>\n",
+       "      <td>0.679476</td>\n",
+       "      <td>0.632856</td>\n",
+       "      <td>0.651557</td>\n",
+       "      <td>0.654629</td>\n",
+       "      <td>0.694013</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>cg07157107</td>\n",
+       "      <td>CHRNA6</td>\n",
+       "      <td>-0.242190</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg07157107</td>\n",
+       "      <td>0.267253</td>\n",
+       "      <td>0.137766</td>\n",
+       "      <td>0.212442</td>\n",
+       "      <td>0.168600</td>\n",
+       "      <td>0.206781</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.149664</td>\n",
+       "      <td>0.184383</td>\n",
+       "      <td>0.133741</td>\n",
+       "      <td>0.172674</td>\n",
+       "      <td>0.168547</td>\n",
+       "      <td>0.171719</td>\n",
+       "      <td>0.162934</td>\n",
+       "      <td>0.135706</td>\n",
+       "      <td>0.190779</td>\n",
+       "      <td>0.191123</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>cg02295216</td>\n",
+       "      <td>CKLF</td>\n",
+       "      <td>0.172590</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg02295216</td>\n",
+       "      <td>0.363497</td>\n",
+       "      <td>0.260611</td>\n",
+       "      <td>0.309377</td>\n",
+       "      <td>0.350464</td>\n",
+       "      <td>0.317099</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.309767</td>\n",
+       "      <td>0.328551</td>\n",
+       "      <td>0.201410</td>\n",
+       "      <td>0.355441</td>\n",
+       "      <td>0.188960</td>\n",
+       "      <td>0.351395</td>\n",
+       "      <td>0.332551</td>\n",
+       "      <td>0.167575</td>\n",
+       "      <td>0.084872</td>\n",
+       "      <td>0.345495</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>cg19223467</td>\n",
+       "      <td>CLEC9A</td>\n",
+       "      <td>-0.152339</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg19223467</td>\n",
+       "      <td>0.553040</td>\n",
+       "      <td>0.540875</td>\n",
+       "      <td>0.408219</td>\n",
+       "      <td>0.639611</td>\n",
+       "      <td>0.540304</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.434638</td>\n",
+       "      <td>0.389198</td>\n",
+       "      <td>0.576087</td>\n",
+       "      <td>0.677964</td>\n",
+       "      <td>0.564957</td>\n",
+       "      <td>0.549210</td>\n",
+       "      <td>0.517783</td>\n",
+       "      <td>0.663231</td>\n",
+       "      <td>0.433247</td>\n",
+       "      <td>0.553600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>CMTM5</td>\n",
+       "      <td>0.172075</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg23631930</td>\n",
+       "      <td>0.769073</td>\n",
+       "      <td>0.786669</td>\n",
+       "      <td>0.789469</td>\n",
+       "      <td>0.712481</td>\n",
+       "      <td>0.817953</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.784860</td>\n",
+       "      <td>0.789034</td>\n",
+       "      <td>0.795643</td>\n",
+       "      <td>0.783826</td>\n",
+       "      <td>0.758287</td>\n",
+       "      <td>0.820371</td>\n",
+       "      <td>0.762424</td>\n",
+       "      <td>0.798704</td>\n",
+       "      <td>0.803269</td>\n",
+       "      <td>0.778339</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>cg12440062</td>\n",
+       "      <td>CRISP2</td>\n",
+       "      <td>0.200273</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg12440062</td>\n",
+       "      <td>0.486181</td>\n",
+       "      <td>0.466767</td>\n",
+       "      <td>0.658400</td>\n",
+       "      <td>0.518216</td>\n",
+       "      <td>0.593437</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.445182</td>\n",
+       "      <td>0.767513</td>\n",
+       "      <td>0.663110</td>\n",
+       "      <td>0.652559</td>\n",
+       "      <td>0.690339</td>\n",
+       "      <td>0.652818</td>\n",
+       "      <td>0.559369</td>\n",
+       "      <td>0.565027</td>\n",
+       "      <td>0.574367</td>\n",
+       "      <td>0.526302</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>cg21290814</td>\n",
+       "      <td>CRTC1</td>\n",
+       "      <td>-0.160943</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg21290814</td>\n",
+       "      <td>0.218103</td>\n",
+       "      <td>0.124658</td>\n",
+       "      <td>0.194146</td>\n",
+       "      <td>0.151656</td>\n",
+       "      <td>0.246419</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.190325</td>\n",
+       "      <td>0.253511</td>\n",
+       "      <td>0.370957</td>\n",
+       "      <td>0.270400</td>\n",
+       "      <td>0.195377</td>\n",
+       "      <td>0.238683</td>\n",
+       "      <td>0.227245</td>\n",
+       "      <td>0.193281</td>\n",
+       "      <td>0.164008</td>\n",
+       "      <td>0.221216</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>cg01136458</td>\n",
+       "      <td>CSMD1</td>\n",
+       "      <td>-0.183525</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg01136458</td>\n",
+       "      <td>0.562662</td>\n",
+       "      <td>0.342647</td>\n",
+       "      <td>0.405482</td>\n",
+       "      <td>0.538545</td>\n",
+       "      <td>0.451746</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.358178</td>\n",
+       "      <td>0.457632</td>\n",
+       "      <td>0.343035</td>\n",
+       "      <td>0.485002</td>\n",
+       "      <td>0.273328</td>\n",
+       "      <td>0.528276</td>\n",
+       "      <td>0.407212</td>\n",
+       "      <td>0.266982</td>\n",
+       "      <td>0.438324</td>\n",
+       "      <td>0.353390</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>CX3CL1</td>\n",
+       "      <td>0.198136</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg05724197</td>\n",
+       "      <td>0.734243</td>\n",
+       "      <td>0.750670</td>\n",
+       "      <td>0.715007</td>\n",
+       "      <td>0.706211</td>\n",
+       "      <td>0.707622</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.741768</td>\n",
+       "      <td>0.743632</td>\n",
+       "      <td>0.694187</td>\n",
+       "      <td>0.701328</td>\n",
+       "      <td>0.699426</td>\n",
+       "      <td>0.752338</td>\n",
+       "      <td>0.671146</td>\n",
+       "      <td>0.696610</td>\n",
+       "      <td>0.740219</td>\n",
+       "      <td>0.734335</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>cg03003745</td>\n",
+       "      <td>CXCL17</td>\n",
+       "      <td>-0.238256</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg03003745</td>\n",
+       "      <td>0.769774</td>\n",
+       "      <td>0.754771</td>\n",
+       "      <td>0.750923</td>\n",
+       "      <td>0.707897</td>\n",
+       "      <td>0.803780</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.768881</td>\n",
+       "      <td>0.773799</td>\n",
+       "      <td>0.768141</td>\n",
+       "      <td>0.742234</td>\n",
+       "      <td>0.750054</td>\n",
+       "      <td>0.762789</td>\n",
+       "      <td>0.705811</td>\n",
+       "      <td>0.765823</td>\n",
+       "      <td>0.761887</td>\n",
+       "      <td>0.790526</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>cg00213123</td>\n",
+       "      <td>CYP1A1</td>\n",
+       "      <td>0.195047</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg00213123</td>\n",
+       "      <td>0.252718</td>\n",
+       "      <td>0.235994</td>\n",
+       "      <td>0.283559</td>\n",
+       "      <td>0.217079</td>\n",
+       "      <td>0.254952</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.201034</td>\n",
+       "      <td>0.237911</td>\n",
+       "      <td>0.263236</td>\n",
+       "      <td>0.295310</td>\n",
+       "      <td>0.283498</td>\n",
+       "      <td>0.213430</td>\n",
+       "      <td>0.231335</td>\n",
+       "      <td>0.192510</td>\n",
+       "      <td>0.235878</td>\n",
+       "      <td>0.233191</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>cg20051772</td>\n",
+       "      <td>DGKA</td>\n",
+       "      <td>-0.186669</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg20051772</td>\n",
+       "      <td>0.274093</td>\n",
+       "      <td>0.153840</td>\n",
+       "      <td>0.242470</td>\n",
+       "      <td>0.201241</td>\n",
+       "      <td>0.264579</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.258048</td>\n",
+       "      <td>0.268499</td>\n",
+       "      <td>0.180419</td>\n",
+       "      <td>0.263201</td>\n",
+       "      <td>0.220096</td>\n",
+       "      <td>0.274449</td>\n",
+       "      <td>0.238346</td>\n",
+       "      <td>0.214392</td>\n",
+       "      <td>0.289757</td>\n",
+       "      <td>0.282479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>cg13379236</td>\n",
+       "      <td>EGF</td>\n",
+       "      <td>-0.151026</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg13379236</td>\n",
+       "      <td>0.573028</td>\n",
+       "      <td>0.612531</td>\n",
+       "      <td>0.601079</td>\n",
+       "      <td>0.545201</td>\n",
+       "      <td>0.595605</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.628913</td>\n",
+       "      <td>0.603874</td>\n",
+       "      <td>0.709718</td>\n",
+       "      <td>0.643444</td>\n",
+       "      <td>0.648941</td>\n",
+       "      <td>0.628367</td>\n",
+       "      <td>0.611217</td>\n",
+       "      <td>0.625344</td>\n",
+       "      <td>0.631433</td>\n",
+       "      <td>0.643077</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>cg13816423</td>\n",
+       "      <td>FOXP4</td>\n",
+       "      <td>-0.206186</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg13816423</td>\n",
+       "      <td>0.525629</td>\n",
+       "      <td>0.547039</td>\n",
+       "      <td>0.526484</td>\n",
+       "      <td>0.377820</td>\n",
+       "      <td>0.482987</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.491120</td>\n",
+       "      <td>0.508041</td>\n",
+       "      <td>0.477693</td>\n",
+       "      <td>0.493924</td>\n",
+       "      <td>0.573321</td>\n",
+       "      <td>0.507138</td>\n",
+       "      <td>0.560417</td>\n",
+       "      <td>0.566918</td>\n",
+       "      <td>0.536212</td>\n",
+       "      <td>0.405821</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>cg07014349</td>\n",
+       "      <td>GJB5</td>\n",
+       "      <td>0.162041</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg07014349</td>\n",
+       "      <td>0.721767</td>\n",
+       "      <td>0.707736</td>\n",
+       "      <td>0.685455</td>\n",
+       "      <td>0.586987</td>\n",
+       "      <td>0.728675</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.697530</td>\n",
+       "      <td>0.681348</td>\n",
+       "      <td>0.712290</td>\n",
+       "      <td>0.673994</td>\n",
+       "      <td>0.687517</td>\n",
+       "      <td>0.680143</td>\n",
+       "      <td>0.663641</td>\n",
+       "      <td>0.665778</td>\n",
+       "      <td>0.708924</td>\n",
+       "      <td>0.717612</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>cg19772011</td>\n",
+       "      <td>GLP1R</td>\n",
+       "      <td>-0.174030</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg19772011</td>\n",
+       "      <td>0.424933</td>\n",
+       "      <td>0.366848</td>\n",
+       "      <td>0.371132</td>\n",
+       "      <td>0.398409</td>\n",
+       "      <td>0.512713</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.326810</td>\n",
+       "      <td>0.420252</td>\n",
+       "      <td>0.315516</td>\n",
+       "      <td>0.373941</td>\n",
+       "      <td>0.324648</td>\n",
+       "      <td>0.383260</td>\n",
+       "      <td>0.361384</td>\n",
+       "      <td>0.385909</td>\n",
+       "      <td>0.387834</td>\n",
+       "      <td>0.438647</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>cg17413194</td>\n",
+       "      <td>GNA13</td>\n",
+       "      <td>0.174816</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg17413194</td>\n",
+       "      <td>0.892900</td>\n",
+       "      <td>0.924701</td>\n",
+       "      <td>0.900737</td>\n",
+       "      <td>0.927879</td>\n",
+       "      <td>0.894044</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.905600</td>\n",
+       "      <td>0.902015</td>\n",
+       "      <td>0.895452</td>\n",
+       "      <td>0.909865</td>\n",
+       "      <td>0.907532</td>\n",
+       "      <td>0.900753</td>\n",
+       "      <td>0.875808</td>\n",
+       "      <td>0.935679</td>\n",
+       "      <td>0.903922</td>\n",
+       "      <td>0.919369</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>cg04225088</td>\n",
+       "      <td>HIPK3</td>\n",
+       "      <td>0.150001</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg04225088</td>\n",
+       "      <td>0.312370</td>\n",
+       "      <td>0.497848</td>\n",
+       "      <td>0.256887</td>\n",
+       "      <td>0.443426</td>\n",
+       "      <td>0.256834</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.353510</td>\n",
+       "      <td>0.245583</td>\n",
+       "      <td>0.189022</td>\n",
+       "      <td>0.406742</td>\n",
+       "      <td>0.338978</td>\n",
+       "      <td>0.208786</td>\n",
+       "      <td>0.266501</td>\n",
+       "      <td>0.353085</td>\n",
+       "      <td>0.305456</td>\n",
+       "      <td>0.253948</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>cg05818394</td>\n",
+       "      <td>HMGB1</td>\n",
+       "      <td>-0.291705</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg05818394</td>\n",
+       "      <td>0.268786</td>\n",
+       "      <td>0.219602</td>\n",
+       "      <td>0.207522</td>\n",
+       "      <td>0.205676</td>\n",
+       "      <td>0.219931</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.261757</td>\n",
+       "      <td>0.236433</td>\n",
+       "      <td>0.145173</td>\n",
+       "      <td>0.288544</td>\n",
+       "      <td>0.218725</td>\n",
+       "      <td>0.222591</td>\n",
+       "      <td>0.233592</td>\n",
+       "      <td>0.244560</td>\n",
+       "      <td>0.250098</td>\n",
+       "      <td>0.201397</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>cg00727675</td>\n",
+       "      <td>HOXA3</td>\n",
+       "      <td>-0.182567</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg00727675</td>\n",
+       "      <td>0.846111</td>\n",
+       "      <td>0.851785</td>\n",
+       "      <td>0.807337</td>\n",
+       "      <td>0.772323</td>\n",
+       "      <td>0.896772</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.767197</td>\n",
+       "      <td>0.831586</td>\n",
+       "      <td>0.815648</td>\n",
+       "      <td>0.796103</td>\n",
+       "      <td>0.800868</td>\n",
+       "      <td>0.874837</td>\n",
+       "      <td>0.794741</td>\n",
+       "      <td>0.862334</td>\n",
+       "      <td>0.858179</td>\n",
+       "      <td>0.872256</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>cg00239353</td>\n",
+       "      <td>IL32</td>\n",
+       "      <td>0.230341</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg00239353</td>\n",
+       "      <td>0.801055</td>\n",
+       "      <td>0.707905</td>\n",
+       "      <td>0.728506</td>\n",
+       "      <td>0.685146</td>\n",
+       "      <td>0.777805</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.761856</td>\n",
+       "      <td>0.766555</td>\n",
+       "      <td>0.808789</td>\n",
+       "      <td>0.725277</td>\n",
+       "      <td>0.739066</td>\n",
+       "      <td>0.823395</td>\n",
+       "      <td>0.731399</td>\n",
+       "      <td>0.783274</td>\n",
+       "      <td>0.808959</td>\n",
+       "      <td>0.809296</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>cg15059851</td>\n",
+       "      <td>IVL</td>\n",
+       "      <td>-0.208371</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg15059851</td>\n",
+       "      <td>0.746068</td>\n",
+       "      <td>0.703093</td>\n",
+       "      <td>0.742771</td>\n",
+       "      <td>0.674082</td>\n",
+       "      <td>0.790157</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.713262</td>\n",
+       "      <td>0.742211</td>\n",
+       "      <td>0.776202</td>\n",
+       "      <td>0.724440</td>\n",
+       "      <td>0.703877</td>\n",
+       "      <td>0.810116</td>\n",
+       "      <td>0.721771</td>\n",
+       "      <td>0.745249</td>\n",
+       "      <td>0.779341</td>\n",
+       "      <td>0.793993</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>cg11775521</td>\n",
+       "      <td>KCNE3</td>\n",
+       "      <td>0.263576</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg11775521</td>\n",
+       "      <td>0.224705</td>\n",
+       "      <td>0.321265</td>\n",
+       "      <td>0.292456</td>\n",
+       "      <td>0.304315</td>\n",
+       "      <td>0.221854</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.262763</td>\n",
+       "      <td>0.262728</td>\n",
+       "      <td>0.279741</td>\n",
+       "      <td>0.347049</td>\n",
+       "      <td>0.318857</td>\n",
+       "      <td>0.191190</td>\n",
+       "      <td>0.254092</td>\n",
+       "      <td>0.322475</td>\n",
+       "      <td>0.230785</td>\n",
+       "      <td>0.207241</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>cg08375658</td>\n",
+       "      <td>KLK12</td>\n",
+       "      <td>-0.150620</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg08375658</td>\n",
+       "      <td>0.373531</td>\n",
+       "      <td>0.369187</td>\n",
+       "      <td>0.405792</td>\n",
+       "      <td>0.229373</td>\n",
+       "      <td>0.320706</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.369314</td>\n",
+       "      <td>0.374514</td>\n",
+       "      <td>0.362033</td>\n",
+       "      <td>0.405099</td>\n",
+       "      <td>0.339099</td>\n",
+       "      <td>0.385131</td>\n",
+       "      <td>0.336779</td>\n",
+       "      <td>0.342804</td>\n",
+       "      <td>0.356646</td>\n",
+       "      <td>0.276763</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>cg07925549</td>\n",
+       "      <td>KRT75</td>\n",
+       "      <td>-0.170578</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg07925549</td>\n",
+       "      <td>0.719333</td>\n",
+       "      <td>0.755092</td>\n",
+       "      <td>0.719713</td>\n",
+       "      <td>0.661375</td>\n",
+       "      <td>0.686504</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.703808</td>\n",
+       "      <td>0.761950</td>\n",
+       "      <td>0.660728</td>\n",
+       "      <td>0.665314</td>\n",
+       "      <td>0.662328</td>\n",
+       "      <td>0.721944</td>\n",
+       "      <td>0.635651</td>\n",
+       "      <td>0.739437</td>\n",
+       "      <td>0.680937</td>\n",
+       "      <td>0.678479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>cg24296478</td>\n",
+       "      <td>LCOR</td>\n",
+       "      <td>-0.157586</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg24296478</td>\n",
+       "      <td>0.123775</td>\n",
+       "      <td>0.113582</td>\n",
+       "      <td>0.098122</td>\n",
+       "      <td>0.061366</td>\n",
+       "      <td>0.202207</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.142852</td>\n",
+       "      <td>0.173247</td>\n",
+       "      <td>0.070762</td>\n",
+       "      <td>0.083220</td>\n",
+       "      <td>0.103510</td>\n",
+       "      <td>0.111210</td>\n",
+       "      <td>0.082034</td>\n",
+       "      <td>0.157397</td>\n",
+       "      <td>0.177708</td>\n",
+       "      <td>0.151386</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>cg23792592</td>\n",
+       "      <td>MIR1-1</td>\n",
+       "      <td>-0.180821</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg23792592</td>\n",
+       "      <td>0.820852</td>\n",
+       "      <td>0.818481</td>\n",
+       "      <td>0.816022</td>\n",
+       "      <td>0.779456</td>\n",
+       "      <td>0.827824</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.845347</td>\n",
+       "      <td>0.816827</td>\n",
+       "      <td>0.803982</td>\n",
+       "      <td>0.789567</td>\n",
+       "      <td>0.816800</td>\n",
+       "      <td>0.851628</td>\n",
+       "      <td>0.799465</td>\n",
+       "      <td>0.834424</td>\n",
+       "      <td>0.845007</td>\n",
+       "      <td>0.821329</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>cg19157647</td>\n",
+       "      <td>MIR1180</td>\n",
+       "      <td>0.157648</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg19157647</td>\n",
+       "      <td>0.848589</td>\n",
+       "      <td>0.877015</td>\n",
+       "      <td>0.859423</td>\n",
+       "      <td>0.795065</td>\n",
+       "      <td>0.855516</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.850693</td>\n",
+       "      <td>0.844363</td>\n",
+       "      <td>0.806228</td>\n",
+       "      <td>0.841611</td>\n",
+       "      <td>0.808398</td>\n",
+       "      <td>0.828929</td>\n",
+       "      <td>0.822029</td>\n",
+       "      <td>0.835106</td>\n",
+       "      <td>0.845336</td>\n",
+       "      <td>0.820117</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>cg11201447</td>\n",
+       "      <td>MIR1204</td>\n",
+       "      <td>-0.298594</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg11201447</td>\n",
+       "      <td>0.563153</td>\n",
+       "      <td>0.390281</td>\n",
+       "      <td>0.503120</td>\n",
+       "      <td>0.383873</td>\n",
+       "      <td>0.501025</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.436112</td>\n",
+       "      <td>0.495300</td>\n",
+       "      <td>0.504980</td>\n",
+       "      <td>0.411687</td>\n",
+       "      <td>0.348005</td>\n",
+       "      <td>0.310327</td>\n",
+       "      <td>0.495870</td>\n",
+       "      <td>0.441954</td>\n",
+       "      <td>0.575405</td>\n",
+       "      <td>0.536525</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>MIR124-3</td>\n",
+       "      <td>0.177844</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg04927004</td>\n",
+       "      <td>0.269138</td>\n",
+       "      <td>0.325553</td>\n",
+       "      <td>0.395209</td>\n",
+       "      <td>0.331040</td>\n",
+       "      <td>0.234604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.335093</td>\n",
+       "      <td>0.304882</td>\n",
+       "      <td>0.398268</td>\n",
+       "      <td>0.321550</td>\n",
+       "      <td>0.344642</td>\n",
+       "      <td>0.260215</td>\n",
+       "      <td>0.318819</td>\n",
+       "      <td>0.286698</td>\n",
+       "      <td>0.262091</td>\n",
+       "      <td>0.357024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>cg10734581</td>\n",
+       "      <td>MIR134</td>\n",
+       "      <td>-0.266630</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg10734581</td>\n",
+       "      <td>0.605681</td>\n",
+       "      <td>0.586926</td>\n",
+       "      <td>0.606444</td>\n",
+       "      <td>0.550279</td>\n",
+       "      <td>0.658604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.593520</td>\n",
+       "      <td>0.583302</td>\n",
+       "      <td>0.611405</td>\n",
+       "      <td>0.569500</td>\n",
+       "      <td>0.575573</td>\n",
+       "      <td>0.645497</td>\n",
+       "      <td>0.591308</td>\n",
+       "      <td>0.576784</td>\n",
+       "      <td>0.660405</td>\n",
+       "      <td>0.639335</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>cg24702147</td>\n",
+       "      <td>MIR141</td>\n",
+       "      <td>-0.157450</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg24702147</td>\n",
+       "      <td>0.833630</td>\n",
+       "      <td>0.878846</td>\n",
+       "      <td>0.819428</td>\n",
+       "      <td>0.824717</td>\n",
+       "      <td>0.859967</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.811076</td>\n",
+       "      <td>0.827837</td>\n",
+       "      <td>0.886588</td>\n",
+       "      <td>0.902918</td>\n",
+       "      <td>0.890800</td>\n",
+       "      <td>0.847578</td>\n",
+       "      <td>0.816638</td>\n",
+       "      <td>0.870090</td>\n",
+       "      <td>0.854882</td>\n",
+       "      <td>0.887010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>cg16570507</td>\n",
+       "      <td>MIR346</td>\n",
+       "      <td>-0.179525</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg16570507</td>\n",
+       "      <td>0.442559</td>\n",
+       "      <td>0.388921</td>\n",
+       "      <td>0.391081</td>\n",
+       "      <td>0.265650</td>\n",
+       "      <td>0.431357</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.371349</td>\n",
+       "      <td>0.297244</td>\n",
+       "      <td>0.282506</td>\n",
+       "      <td>0.365149</td>\n",
+       "      <td>0.355487</td>\n",
+       "      <td>0.381577</td>\n",
+       "      <td>0.310171</td>\n",
+       "      <td>0.354487</td>\n",
+       "      <td>0.418710</td>\n",
+       "      <td>0.302428</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>cg02577745</td>\n",
+       "      <td>MIR493</td>\n",
+       "      <td>-0.163426</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg02577745</td>\n",
+       "      <td>0.855403</td>\n",
+       "      <td>0.823589</td>\n",
+       "      <td>0.862462</td>\n",
+       "      <td>0.836489</td>\n",
+       "      <td>0.877253</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.864000</td>\n",
+       "      <td>0.808004</td>\n",
+       "      <td>0.848807</td>\n",
+       "      <td>0.807441</td>\n",
+       "      <td>0.836581</td>\n",
+       "      <td>0.891960</td>\n",
+       "      <td>0.825203</td>\n",
+       "      <td>0.837047</td>\n",
+       "      <td>0.865457</td>\n",
+       "      <td>0.870827</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>cg22500132</td>\n",
+       "      <td>MUC1</td>\n",
+       "      <td>-0.282771</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg22500132</td>\n",
+       "      <td>0.113111</td>\n",
+       "      <td>0.100479</td>\n",
+       "      <td>0.107500</td>\n",
+       "      <td>0.095274</td>\n",
+       "      <td>0.090260</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.067399</td>\n",
+       "      <td>0.094780</td>\n",
+       "      <td>0.128484</td>\n",
+       "      <td>0.109636</td>\n",
+       "      <td>0.113056</td>\n",
+       "      <td>0.081551</td>\n",
+       "      <td>0.124542</td>\n",
+       "      <td>0.088530</td>\n",
+       "      <td>0.095734</td>\n",
+       "      <td>0.120762</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>cg21298408</td>\n",
+       "      <td>NAT1</td>\n",
+       "      <td>-0.159201</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg21298408</td>\n",
+       "      <td>0.710126</td>\n",
+       "      <td>0.791803</td>\n",
+       "      <td>0.719930</td>\n",
+       "      <td>0.742611</td>\n",
+       "      <td>0.739981</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.753892</td>\n",
+       "      <td>0.734089</td>\n",
+       "      <td>0.652814</td>\n",
+       "      <td>0.703415</td>\n",
+       "      <td>0.683536</td>\n",
+       "      <td>0.736089</td>\n",
+       "      <td>0.716511</td>\n",
+       "      <td>0.667518</td>\n",
+       "      <td>0.738462</td>\n",
+       "      <td>0.717654</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>cg07552803</td>\n",
+       "      <td>NEFM</td>\n",
+       "      <td>0.227250</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg07552803</td>\n",
+       "      <td>0.099552</td>\n",
+       "      <td>0.112437</td>\n",
+       "      <td>0.132645</td>\n",
+       "      <td>0.133998</td>\n",
+       "      <td>0.064870</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.108710</td>\n",
+       "      <td>0.114184</td>\n",
+       "      <td>0.148561</td>\n",
+       "      <td>0.140304</td>\n",
+       "      <td>0.124437</td>\n",
+       "      <td>0.070857</td>\n",
+       "      <td>0.086668</td>\n",
+       "      <td>0.090281</td>\n",
+       "      <td>0.102663</td>\n",
+       "      <td>0.130862</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>cg08317412</td>\n",
+       "      <td>PANX3</td>\n",
+       "      <td>-0.169833</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg08317412</td>\n",
+       "      <td>0.798718</td>\n",
+       "      <td>0.795126</td>\n",
+       "      <td>0.795669</td>\n",
+       "      <td>0.760310</td>\n",
+       "      <td>0.799150</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.820026</td>\n",
+       "      <td>0.767582</td>\n",
+       "      <td>0.801853</td>\n",
+       "      <td>0.779158</td>\n",
+       "      <td>0.823689</td>\n",
+       "      <td>0.820692</td>\n",
+       "      <td>0.746107</td>\n",
+       "      <td>0.772055</td>\n",
+       "      <td>0.805236</td>\n",
+       "      <td>0.810853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>cg20248866</td>\n",
+       "      <td>PCYT2</td>\n",
+       "      <td>0.154787</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg20248866</td>\n",
+       "      <td>0.379558</td>\n",
+       "      <td>0.515408</td>\n",
+       "      <td>0.424047</td>\n",
+       "      <td>0.411715</td>\n",
+       "      <td>0.379275</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.387834</td>\n",
+       "      <td>0.392653</td>\n",
+       "      <td>0.415538</td>\n",
+       "      <td>0.474268</td>\n",
+       "      <td>0.401104</td>\n",
+       "      <td>0.440038</td>\n",
+       "      <td>0.394245</td>\n",
+       "      <td>0.408708</td>\n",
+       "      <td>0.420681</td>\n",
+       "      <td>0.442299</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>cg07211259</td>\n",
+       "      <td>PDCD1LG2</td>\n",
+       "      <td>0.152846</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg07211259</td>\n",
+       "      <td>0.182180</td>\n",
+       "      <td>0.102735</td>\n",
+       "      <td>0.158707</td>\n",
+       "      <td>0.176757</td>\n",
+       "      <td>0.212701</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.217170</td>\n",
+       "      <td>0.122523</td>\n",
+       "      <td>0.145827</td>\n",
+       "      <td>0.121878</td>\n",
+       "      <td>0.161302</td>\n",
+       "      <td>0.132285</td>\n",
+       "      <td>0.096186</td>\n",
+       "      <td>0.201539</td>\n",
+       "      <td>0.198195</td>\n",
+       "      <td>0.167421</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>cg12871376</td>\n",
+       "      <td>PGC</td>\n",
+       "      <td>-0.152930</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg12871376</td>\n",
+       "      <td>0.634038</td>\n",
+       "      <td>0.690147</td>\n",
+       "      <td>0.610273</td>\n",
+       "      <td>0.642777</td>\n",
+       "      <td>0.664123</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.621354</td>\n",
+       "      <td>0.591425</td>\n",
+       "      <td>0.587441</td>\n",
+       "      <td>0.616403</td>\n",
+       "      <td>0.620384</td>\n",
+       "      <td>0.637948</td>\n",
+       "      <td>0.629167</td>\n",
+       "      <td>0.640783</td>\n",
+       "      <td>0.648596</td>\n",
+       "      <td>0.611541</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>cg02329916</td>\n",
+       "      <td>PRSS1</td>\n",
+       "      <td>-0.206755</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg02329916</td>\n",
+       "      <td>0.697635</td>\n",
+       "      <td>0.804495</td>\n",
+       "      <td>0.774227</td>\n",
+       "      <td>0.735544</td>\n",
+       "      <td>0.766629</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.770766</td>\n",
+       "      <td>0.763897</td>\n",
+       "      <td>0.751401</td>\n",
+       "      <td>0.726040</td>\n",
+       "      <td>0.715777</td>\n",
+       "      <td>0.766721</td>\n",
+       "      <td>0.720330</td>\n",
+       "      <td>0.705289</td>\n",
+       "      <td>0.712917</td>\n",
+       "      <td>0.718007</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>cg22746058</td>\n",
+       "      <td>PTF1A</td>\n",
+       "      <td>0.189984</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg22746058</td>\n",
+       "      <td>0.091921</td>\n",
+       "      <td>0.112488</td>\n",
+       "      <td>0.117563</td>\n",
+       "      <td>0.143644</td>\n",
+       "      <td>0.066142</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.105599</td>\n",
+       "      <td>0.120432</td>\n",
+       "      <td>0.160880</td>\n",
+       "      <td>0.148633</td>\n",
+       "      <td>0.109012</td>\n",
+       "      <td>0.082206</td>\n",
+       "      <td>0.119163</td>\n",
+       "      <td>0.092386</td>\n",
+       "      <td>0.098278</td>\n",
+       "      <td>0.134826</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>cg05506480</td>\n",
+       "      <td>RAB6B</td>\n",
+       "      <td>-0.195065</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg05506480</td>\n",
+       "      <td>0.178189</td>\n",
+       "      <td>0.157084</td>\n",
+       "      <td>0.094172</td>\n",
+       "      <td>0.140586</td>\n",
+       "      <td>0.110955</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.131170</td>\n",
+       "      <td>0.092109</td>\n",
+       "      <td>0.091508</td>\n",
+       "      <td>0.197731</td>\n",
+       "      <td>0.130661</td>\n",
+       "      <td>0.134397</td>\n",
+       "      <td>0.164433</td>\n",
+       "      <td>0.137992</td>\n",
+       "      <td>0.151490</td>\n",
+       "      <td>0.111528</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>cg26106778</td>\n",
+       "      <td>RING1</td>\n",
+       "      <td>0.186264</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg26106778</td>\n",
+       "      <td>0.169706</td>\n",
+       "      <td>0.206504</td>\n",
+       "      <td>0.211555</td>\n",
+       "      <td>0.233968</td>\n",
+       "      <td>0.139397</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.188477</td>\n",
+       "      <td>0.189869</td>\n",
+       "      <td>0.187904</td>\n",
+       "      <td>0.237459</td>\n",
+       "      <td>0.231120</td>\n",
+       "      <td>0.146278</td>\n",
+       "      <td>0.177644</td>\n",
+       "      <td>0.214431</td>\n",
+       "      <td>0.148552</td>\n",
+       "      <td>0.203391</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>cg05884032</td>\n",
+       "      <td>SALL3</td>\n",
+       "      <td>0.151857</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg05884032</td>\n",
+       "      <td>0.170969</td>\n",
+       "      <td>0.175475</td>\n",
+       "      <td>0.161222</td>\n",
+       "      <td>0.214139</td>\n",
+       "      <td>0.145597</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.152065</td>\n",
+       "      <td>0.148380</td>\n",
+       "      <td>0.330124</td>\n",
+       "      <td>0.210860</td>\n",
+       "      <td>0.208232</td>\n",
+       "      <td>0.154013</td>\n",
+       "      <td>0.217560</td>\n",
+       "      <td>0.167469</td>\n",
+       "      <td>0.114794</td>\n",
+       "      <td>0.214311</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>cg20596724</td>\n",
+       "      <td>SDR9C7</td>\n",
+       "      <td>-0.198220</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg20596724</td>\n",
+       "      <td>0.852856</td>\n",
+       "      <td>0.831449</td>\n",
+       "      <td>0.827896</td>\n",
+       "      <td>0.786247</td>\n",
+       "      <td>0.860701</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.873213</td>\n",
+       "      <td>0.836710</td>\n",
+       "      <td>0.790930</td>\n",
+       "      <td>0.809666</td>\n",
+       "      <td>0.855393</td>\n",
+       "      <td>0.854654</td>\n",
+       "      <td>0.815397</td>\n",
+       "      <td>0.848365</td>\n",
+       "      <td>0.855520</td>\n",
+       "      <td>0.900632</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>cg16536739</td>\n",
+       "      <td>SFRP5</td>\n",
+       "      <td>-0.152947</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg16536739</td>\n",
+       "      <td>0.701835</td>\n",
+       "      <td>0.644866</td>\n",
+       "      <td>0.695675</td>\n",
+       "      <td>0.631480</td>\n",
+       "      <td>0.690910</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.669946</td>\n",
+       "      <td>0.638430</td>\n",
+       "      <td>0.700145</td>\n",
+       "      <td>0.649333</td>\n",
+       "      <td>0.657203</td>\n",
+       "      <td>0.748811</td>\n",
+       "      <td>0.702383</td>\n",
+       "      <td>0.675559</td>\n",
+       "      <td>0.747703</td>\n",
+       "      <td>0.709482</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>cg04433322</td>\n",
+       "      <td>SLC4A1</td>\n",
+       "      <td>-0.211638</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg04433322</td>\n",
+       "      <td>0.693354</td>\n",
+       "      <td>0.620378</td>\n",
+       "      <td>0.640691</td>\n",
+       "      <td>0.538186</td>\n",
+       "      <td>0.690076</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.655099</td>\n",
+       "      <td>0.595588</td>\n",
+       "      <td>0.636928</td>\n",
+       "      <td>0.594470</td>\n",
+       "      <td>0.605271</td>\n",
+       "      <td>0.694352</td>\n",
+       "      <td>0.625864</td>\n",
+       "      <td>0.584421</td>\n",
+       "      <td>0.673791</td>\n",
+       "      <td>0.628553</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>cg02547394</td>\n",
+       "      <td>SOX1</td>\n",
+       "      <td>0.228038</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg02547394</td>\n",
+       "      <td>0.216667</td>\n",
+       "      <td>0.343825</td>\n",
+       "      <td>0.321606</td>\n",
+       "      <td>0.272403</td>\n",
+       "      <td>0.195273</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.239604</td>\n",
+       "      <td>0.287996</td>\n",
+       "      <td>0.350911</td>\n",
+       "      <td>0.334620</td>\n",
+       "      <td>0.288577</td>\n",
+       "      <td>0.200789</td>\n",
+       "      <td>0.275149</td>\n",
+       "      <td>0.233916</td>\n",
+       "      <td>0.192863</td>\n",
+       "      <td>0.304376</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>54</th>\n",
+       "      <td>cg12610471</td>\n",
+       "      <td>SPAG6</td>\n",
+       "      <td>0.281363</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg12610471</td>\n",
+       "      <td>0.241770</td>\n",
+       "      <td>0.257214</td>\n",
+       "      <td>0.282535</td>\n",
+       "      <td>0.297399</td>\n",
+       "      <td>0.247937</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.214455</td>\n",
+       "      <td>0.254438</td>\n",
+       "      <td>0.280705</td>\n",
+       "      <td>0.316664</td>\n",
+       "      <td>0.265764</td>\n",
+       "      <td>0.248576</td>\n",
+       "      <td>0.278403</td>\n",
+       "      <td>0.269248</td>\n",
+       "      <td>0.244609</td>\n",
+       "      <td>0.286878</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>55</th>\n",
+       "      <td>cg06314202</td>\n",
+       "      <td>SSTR5</td>\n",
+       "      <td>-0.208831</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg06314202</td>\n",
+       "      <td>0.764468</td>\n",
+       "      <td>0.799973</td>\n",
+       "      <td>0.729717</td>\n",
+       "      <td>0.740498</td>\n",
+       "      <td>0.763586</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.747278</td>\n",
+       "      <td>0.753389</td>\n",
+       "      <td>0.785326</td>\n",
+       "      <td>0.734076</td>\n",
+       "      <td>0.695954</td>\n",
+       "      <td>0.801029</td>\n",
+       "      <td>0.754678</td>\n",
+       "      <td>0.776418</td>\n",
+       "      <td>0.751647</td>\n",
+       "      <td>0.727862</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56</th>\n",
+       "      <td>cg06447795</td>\n",
+       "      <td>TGM2</td>\n",
+       "      <td>-0.193115</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg06447795</td>\n",
+       "      <td>0.044252</td>\n",
+       "      <td>0.029781</td>\n",
+       "      <td>0.069850</td>\n",
+       "      <td>0.139260</td>\n",
+       "      <td>0.094534</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.067412</td>\n",
+       "      <td>0.064750</td>\n",
+       "      <td>0.082407</td>\n",
+       "      <td>0.074641</td>\n",
+       "      <td>0.041037</td>\n",
+       "      <td>0.082432</td>\n",
+       "      <td>0.125600</td>\n",
+       "      <td>0.037847</td>\n",
+       "      <td>0.044367</td>\n",
+       "      <td>0.092974</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57</th>\n",
+       "      <td>cg14153654</td>\n",
+       "      <td>TNFRSF9</td>\n",
+       "      <td>-0.195903</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>cg14153654</td>\n",
+       "      <td>0.507465</td>\n",
+       "      <td>0.342007</td>\n",
+       "      <td>0.329841</td>\n",
+       "      <td>0.337737</td>\n",
+       "      <td>0.417720</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.413682</td>\n",
+       "      <td>0.368481</td>\n",
+       "      <td>0.387365</td>\n",
+       "      <td>0.363083</td>\n",
+       "      <td>0.382316</td>\n",
+       "      <td>0.447347</td>\n",
+       "      <td>0.433817</td>\n",
+       "      <td>0.306990</td>\n",
+       "      <td>0.424064</td>\n",
+       "      <td>0.346655</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58</th>\n",
+       "      <td>cg24073122</td>\n",
+       "      <td>TP73</td>\n",
+       "      <td>0.209996</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg24073122</td>\n",
+       "      <td>0.234215</td>\n",
+       "      <td>0.245132</td>\n",
+       "      <td>0.254275</td>\n",
+       "      <td>0.257438</td>\n",
+       "      <td>0.192703</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.216009</td>\n",
+       "      <td>0.252076</td>\n",
+       "      <td>0.261415</td>\n",
+       "      <td>0.269041</td>\n",
+       "      <td>0.262740</td>\n",
+       "      <td>0.206733</td>\n",
+       "      <td>0.193760</td>\n",
+       "      <td>0.209036</td>\n",
+       "      <td>0.219223</td>\n",
+       "      <td>0.228966</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>59</th>\n",
+       "      <td>cg23571857</td>\n",
+       "      <td>XAF1</td>\n",
+       "      <td>0.216849</td>\n",
+       "      <td>TSS1500</td>\n",
+       "      <td>cg23571857</td>\n",
+       "      <td>0.524199</td>\n",
+       "      <td>0.598047</td>\n",
+       "      <td>0.543003</td>\n",
+       "      <td>0.606595</td>\n",
+       "      <td>0.519143</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.549308</td>\n",
+       "      <td>0.519532</td>\n",
+       "      <td>0.449382</td>\n",
+       "      <td>0.638999</td>\n",
+       "      <td>0.582213</td>\n",
+       "      <td>0.532573</td>\n",
+       "      <td>0.501536</td>\n",
+       "      <td>0.559082</td>\n",
+       "      <td>0.570046</td>\n",
+       "      <td>0.600431</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>60 rows × 423 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            ID      gene     dbeta  feature  Unnamed: 0         0         1  \\\n",
+       "0   cg03760483    ALOX12  0.157175   TSS200  cg03760483  0.236414  0.456963   \n",
+       "1   cg00074348     APLNR -0.187434  TSS1500  cg00074348  0.466309  0.457003   \n",
+       "2   cg04290171      CD46 -0.201098  TSS1500  cg04290171  0.889514  0.860040   \n",
+       "3   cg00044665      CDH5  0.206568   TSS200  cg00044665  0.266689  0.332246   \n",
+       "4   cg14666310   CEACAM5 -0.210341  TSS1500  cg14666310  0.673555  0.695180   \n",
+       "5   cg07157107    CHRNA6 -0.242190   TSS200  cg07157107  0.267253  0.137766   \n",
+       "6   cg02295216      CKLF  0.172590  TSS1500  cg02295216  0.363497  0.260611   \n",
+       "7   cg19223467    CLEC9A -0.152339   TSS200  cg19223467  0.553040  0.540875   \n",
+       "8   cg23631930     CMTM5  0.172075   TSS200  cg23631930  0.769073  0.786669   \n",
+       "9   cg12440062    CRISP2  0.200273   TSS200  cg12440062  0.486181  0.466767   \n",
+       "10  cg21290814     CRTC1 -0.160943  TSS1500  cg21290814  0.218103  0.124658   \n",
+       "11  cg01136458     CSMD1 -0.183525  TSS1500  cg01136458  0.562662  0.342647   \n",
+       "12  cg05724197    CX3CL1  0.198136  TSS1500  cg05724197  0.734243  0.750670   \n",
+       "13  cg03003745    CXCL17 -0.238256  TSS1500  cg03003745  0.769774  0.754771   \n",
+       "14  cg00213123    CYP1A1  0.195047  TSS1500  cg00213123  0.252718  0.235994   \n",
+       "15  cg20051772      DGKA -0.186669  TSS1500  cg20051772  0.274093  0.153840   \n",
+       "16  cg13379236       EGF -0.151026  TSS1500  cg13379236  0.573028  0.612531   \n",
+       "17  cg13816423     FOXP4 -0.206186  TSS1500  cg13816423  0.525629  0.547039   \n",
+       "18  cg07014349      GJB5  0.162041   TSS200  cg07014349  0.721767  0.707736   \n",
+       "19  cg19772011     GLP1R -0.174030  TSS1500  cg19772011  0.424933  0.366848   \n",
+       "20  cg17413194     GNA13  0.174816  TSS1500  cg17413194  0.892900  0.924701   \n",
+       "21  cg04225088     HIPK3  0.150001  TSS1500  cg04225088  0.312370  0.497848   \n",
+       "22  cg05818394     HMGB1 -0.291705  TSS1500  cg05818394  0.268786  0.219602   \n",
+       "23  cg00727675     HOXA3 -0.182567  TSS1500  cg00727675  0.846111  0.851785   \n",
+       "24  cg00239353      IL32  0.230341  TSS1500  cg00239353  0.801055  0.707905   \n",
+       "25  cg15059851       IVL -0.208371  TSS1500  cg15059851  0.746068  0.703093   \n",
+       "26  cg11775521     KCNE3  0.263576   TSS200  cg11775521  0.224705  0.321265   \n",
+       "27  cg08375658     KLK12 -0.150620  TSS1500  cg08375658  0.373531  0.369187   \n",
+       "28  cg07925549     KRT75 -0.170578  TSS1500  cg07925549  0.719333  0.755092   \n",
+       "29  cg24296478      LCOR -0.157586  TSS1500  cg24296478  0.123775  0.113582   \n",
+       "30  cg23792592    MIR1-1 -0.180821  TSS1500  cg23792592  0.820852  0.818481   \n",
+       "31  cg19157647   MIR1180  0.157648   TSS200  cg19157647  0.848589  0.877015   \n",
+       "32  cg11201447   MIR1204 -0.298594   TSS200  cg11201447  0.563153  0.390281   \n",
+       "33  cg04927004  MIR124-3  0.177844  TSS1500  cg04927004  0.269138  0.325553   \n",
+       "34  cg10734581    MIR134 -0.266630  TSS1500  cg10734581  0.605681  0.586926   \n",
+       "35  cg24702147    MIR141 -0.157450  TSS1500  cg24702147  0.833630  0.878846   \n",
+       "36  cg16570507    MIR346 -0.179525   TSS200  cg16570507  0.442559  0.388921   \n",
+       "37  cg02577745    MIR493 -0.163426  TSS1500  cg02577745  0.855403  0.823589   \n",
+       "38  cg22500132      MUC1 -0.282771   TSS200  cg22500132  0.113111  0.100479   \n",
+       "39  cg21298408      NAT1 -0.159201   TSS200  cg21298408  0.710126  0.791803   \n",
+       "40  cg07552803      NEFM  0.227250  TSS1500  cg07552803  0.099552  0.112437   \n",
+       "41  cg08317412     PANX3 -0.169833  TSS1500  cg08317412  0.798718  0.795126   \n",
+       "42  cg20248866     PCYT2  0.154787  TSS1500  cg20248866  0.379558  0.515408   \n",
+       "43  cg07211259  PDCD1LG2  0.152846   TSS200  cg07211259  0.182180  0.102735   \n",
+       "44  cg12871376       PGC -0.152930  TSS1500  cg12871376  0.634038  0.690147   \n",
+       "45  cg02329916     PRSS1 -0.206755   TSS200  cg02329916  0.697635  0.804495   \n",
+       "46  cg22746058     PTF1A  0.189984  TSS1500  cg22746058  0.091921  0.112488   \n",
+       "47  cg05506480     RAB6B -0.195065  TSS1500  cg05506480  0.178189  0.157084   \n",
+       "48  cg26106778     RING1  0.186264  TSS1500  cg26106778  0.169706  0.206504   \n",
+       "49  cg05884032     SALL3  0.151857   TSS200  cg05884032  0.170969  0.175475   \n",
+       "50  cg20596724    SDR9C7 -0.198220  TSS1500  cg20596724  0.852856  0.831449   \n",
+       "51  cg16536739     SFRP5 -0.152947  TSS1500  cg16536739  0.701835  0.644866   \n",
+       "52  cg04433322    SLC4A1 -0.211638  TSS1500  cg04433322  0.693354  0.620378   \n",
+       "53  cg02547394      SOX1  0.228038   TSS200  cg02547394  0.216667  0.343825   \n",
+       "54  cg12610471     SPAG6  0.281363   TSS200  cg12610471  0.241770  0.257214   \n",
+       "55  cg06314202     SSTR5 -0.208831  TSS1500  cg06314202  0.764468  0.799973   \n",
+       "56  cg06447795      TGM2 -0.193115  TSS1500  cg06447795  0.044252  0.029781   \n",
+       "57  cg14153654   TNFRSF9 -0.195903   TSS200  cg14153654  0.507465  0.342007   \n",
+       "58  cg24073122      TP73  0.209996  TSS1500  cg24073122  0.234215  0.245132   \n",
+       "59  cg23571857      XAF1  0.216849  TSS1500  cg23571857  0.524199  0.598047   \n",
+       "\n",
+       "           2         3         4  ...       408       409       410       411  \\\n",
+       "0   0.393205  0.319442  0.376546  ...  0.433266  0.385754  0.365361  0.571618   \n",
+       "1   0.442229  0.460896  0.526294  ...  0.406462  0.468974  0.505998  0.447733   \n",
+       "2   0.825669  0.808767  0.882251  ...  0.897428  0.842283  0.886778  0.903050   \n",
+       "3   0.269771  0.315645  0.234602  ...  0.274103  0.259853  0.229335  0.328268   \n",
+       "4   0.686634  0.641230  0.743104  ...  0.681935  0.613599  0.728985  0.664602   \n",
+       "5   0.212442  0.168600  0.206781  ...  0.149664  0.184383  0.133741  0.172674   \n",
+       "6   0.309377  0.350464  0.317099  ...  0.309767  0.328551  0.201410  0.355441   \n",
+       "7   0.408219  0.639611  0.540304  ...  0.434638  0.389198  0.576087  0.677964   \n",
+       "8   0.789469  0.712481  0.817953  ...  0.784860  0.789034  0.795643  0.783826   \n",
+       "9   0.658400  0.518216  0.593437  ...  0.445182  0.767513  0.663110  0.652559   \n",
+       "10  0.194146  0.151656  0.246419  ...  0.190325  0.253511  0.370957  0.270400   \n",
+       "11  0.405482  0.538545  0.451746  ...  0.358178  0.457632  0.343035  0.485002   \n",
+       "12  0.715007  0.706211  0.707622  ...  0.741768  0.743632  0.694187  0.701328   \n",
+       "13  0.750923  0.707897  0.803780  ...  0.768881  0.773799  0.768141  0.742234   \n",
+       "14  0.283559  0.217079  0.254952  ...  0.201034  0.237911  0.263236  0.295310   \n",
+       "15  0.242470  0.201241  0.264579  ...  0.258048  0.268499  0.180419  0.263201   \n",
+       "16  0.601079  0.545201  0.595605  ...  0.628913  0.603874  0.709718  0.643444   \n",
+       "17  0.526484  0.377820  0.482987  ...  0.491120  0.508041  0.477693  0.493924   \n",
+       "18  0.685455  0.586987  0.728675  ...  0.697530  0.681348  0.712290  0.673994   \n",
+       "19  0.371132  0.398409  0.512713  ...  0.326810  0.420252  0.315516  0.373941   \n",
+       "20  0.900737  0.927879  0.894044  ...  0.905600  0.902015  0.895452  0.909865   \n",
+       "21  0.256887  0.443426  0.256834  ...  0.353510  0.245583  0.189022  0.406742   \n",
+       "22  0.207522  0.205676  0.219931  ...  0.261757  0.236433  0.145173  0.288544   \n",
+       "23  0.807337  0.772323  0.896772  ...  0.767197  0.831586  0.815648  0.796103   \n",
+       "24  0.728506  0.685146  0.777805  ...  0.761856  0.766555  0.808789  0.725277   \n",
+       "25  0.742771  0.674082  0.790157  ...  0.713262  0.742211  0.776202  0.724440   \n",
+       "26  0.292456  0.304315  0.221854  ...  0.262763  0.262728  0.279741  0.347049   \n",
+       "27  0.405792  0.229373  0.320706  ...  0.369314  0.374514  0.362033  0.405099   \n",
+       "28  0.719713  0.661375  0.686504  ...  0.703808  0.761950  0.660728  0.665314   \n",
+       "29  0.098122  0.061366  0.202207  ...  0.142852  0.173247  0.070762  0.083220   \n",
+       "30  0.816022  0.779456  0.827824  ...  0.845347  0.816827  0.803982  0.789567   \n",
+       "31  0.859423  0.795065  0.855516  ...  0.850693  0.844363  0.806228  0.841611   \n",
+       "32  0.503120  0.383873  0.501025  ...  0.436112  0.495300  0.504980  0.411687   \n",
+       "33  0.395209  0.331040  0.234604  ...  0.335093  0.304882  0.398268  0.321550   \n",
+       "34  0.606444  0.550279  0.658604  ...  0.593520  0.583302  0.611405  0.569500   \n",
+       "35  0.819428  0.824717  0.859967  ...  0.811076  0.827837  0.886588  0.902918   \n",
+       "36  0.391081  0.265650  0.431357  ...  0.371349  0.297244  0.282506  0.365149   \n",
+       "37  0.862462  0.836489  0.877253  ...  0.864000  0.808004  0.848807  0.807441   \n",
+       "38  0.107500  0.095274  0.090260  ...  0.067399  0.094780  0.128484  0.109636   \n",
+       "39  0.719930  0.742611  0.739981  ...  0.753892  0.734089  0.652814  0.703415   \n",
+       "40  0.132645  0.133998  0.064870  ...  0.108710  0.114184  0.148561  0.140304   \n",
+       "41  0.795669  0.760310  0.799150  ...  0.820026  0.767582  0.801853  0.779158   \n",
+       "42  0.424047  0.411715  0.379275  ...  0.387834  0.392653  0.415538  0.474268   \n",
+       "43  0.158707  0.176757  0.212701  ...  0.217170  0.122523  0.145827  0.121878   \n",
+       "44  0.610273  0.642777  0.664123  ...  0.621354  0.591425  0.587441  0.616403   \n",
+       "45  0.774227  0.735544  0.766629  ...  0.770766  0.763897  0.751401  0.726040   \n",
+       "46  0.117563  0.143644  0.066142  ...  0.105599  0.120432  0.160880  0.148633   \n",
+       "47  0.094172  0.140586  0.110955  ...  0.131170  0.092109  0.091508  0.197731   \n",
+       "48  0.211555  0.233968  0.139397  ...  0.188477  0.189869  0.187904  0.237459   \n",
+       "49  0.161222  0.214139  0.145597  ...  0.152065  0.148380  0.330124  0.210860   \n",
+       "50  0.827896  0.786247  0.860701  ...  0.873213  0.836710  0.790930  0.809666   \n",
+       "51  0.695675  0.631480  0.690910  ...  0.669946  0.638430  0.700145  0.649333   \n",
+       "52  0.640691  0.538186  0.690076  ...  0.655099  0.595588  0.636928  0.594470   \n",
+       "53  0.321606  0.272403  0.195273  ...  0.239604  0.287996  0.350911  0.334620   \n",
+       "54  0.282535  0.297399  0.247937  ...  0.214455  0.254438  0.280705  0.316664   \n",
+       "55  0.729717  0.740498  0.763586  ...  0.747278  0.753389  0.785326  0.734076   \n",
+       "56  0.069850  0.139260  0.094534  ...  0.067412  0.064750  0.082407  0.074641   \n",
+       "57  0.329841  0.337737  0.417720  ...  0.413682  0.368481  0.387365  0.363083   \n",
+       "58  0.254275  0.257438  0.192703  ...  0.216009  0.252076  0.261415  0.269041   \n",
+       "59  0.543003  0.606595  0.519143  ...  0.549308  0.519532  0.449382  0.638999   \n",
+       "\n",
+       "         412       413       414       415       416       417  \n",
+       "0   0.389705  0.376265  0.200213  0.213818  0.223605  0.390453  \n",
+       "1   0.496243  0.516885  0.478009  0.461991  0.505650  0.425387  \n",
+       "2   0.897832  0.819984  0.803872  0.918829  0.854414  0.911942  \n",
+       "3   0.299035  0.222106  0.224438  0.277983  0.251191  0.253250  \n",
+       "4   0.685677  0.679476  0.632856  0.651557  0.654629  0.694013  \n",
+       "5   0.168547  0.171719  0.162934  0.135706  0.190779  0.191123  \n",
+       "6   0.188960  0.351395  0.332551  0.167575  0.084872  0.345495  \n",
+       "7   0.564957  0.549210  0.517783  0.663231  0.433247  0.553600  \n",
+       "8   0.758287  0.820371  0.762424  0.798704  0.803269  0.778339  \n",
+       "9   0.690339  0.652818  0.559369  0.565027  0.574367  0.526302  \n",
+       "10  0.195377  0.238683  0.227245  0.193281  0.164008  0.221216  \n",
+       "11  0.273328  0.528276  0.407212  0.266982  0.438324  0.353390  \n",
+       "12  0.699426  0.752338  0.671146  0.696610  0.740219  0.734335  \n",
+       "13  0.750054  0.762789  0.705811  0.765823  0.761887  0.790526  \n",
+       "14  0.283498  0.213430  0.231335  0.192510  0.235878  0.233191  \n",
+       "15  0.220096  0.274449  0.238346  0.214392  0.289757  0.282479  \n",
+       "16  0.648941  0.628367  0.611217  0.625344  0.631433  0.643077  \n",
+       "17  0.573321  0.507138  0.560417  0.566918  0.536212  0.405821  \n",
+       "18  0.687517  0.680143  0.663641  0.665778  0.708924  0.717612  \n",
+       "19  0.324648  0.383260  0.361384  0.385909  0.387834  0.438647  \n",
+       "20  0.907532  0.900753  0.875808  0.935679  0.903922  0.919369  \n",
+       "21  0.338978  0.208786  0.266501  0.353085  0.305456  0.253948  \n",
+       "22  0.218725  0.222591  0.233592  0.244560  0.250098  0.201397  \n",
+       "23  0.800868  0.874837  0.794741  0.862334  0.858179  0.872256  \n",
+       "24  0.739066  0.823395  0.731399  0.783274  0.808959  0.809296  \n",
+       "25  0.703877  0.810116  0.721771  0.745249  0.779341  0.793993  \n",
+       "26  0.318857  0.191190  0.254092  0.322475  0.230785  0.207241  \n",
+       "27  0.339099  0.385131  0.336779  0.342804  0.356646  0.276763  \n",
+       "28  0.662328  0.721944  0.635651  0.739437  0.680937  0.678479  \n",
+       "29  0.103510  0.111210  0.082034  0.157397  0.177708  0.151386  \n",
+       "30  0.816800  0.851628  0.799465  0.834424  0.845007  0.821329  \n",
+       "31  0.808398  0.828929  0.822029  0.835106  0.845336  0.820117  \n",
+       "32  0.348005  0.310327  0.495870  0.441954  0.575405  0.536525  \n",
+       "33  0.344642  0.260215  0.318819  0.286698  0.262091  0.357024  \n",
+       "34  0.575573  0.645497  0.591308  0.576784  0.660405  0.639335  \n",
+       "35  0.890800  0.847578  0.816638  0.870090  0.854882  0.887010  \n",
+       "36  0.355487  0.381577  0.310171  0.354487  0.418710  0.302428  \n",
+       "37  0.836581  0.891960  0.825203  0.837047  0.865457  0.870827  \n",
+       "38  0.113056  0.081551  0.124542  0.088530  0.095734  0.120762  \n",
+       "39  0.683536  0.736089  0.716511  0.667518  0.738462  0.717654  \n",
+       "40  0.124437  0.070857  0.086668  0.090281  0.102663  0.130862  \n",
+       "41  0.823689  0.820692  0.746107  0.772055  0.805236  0.810853  \n",
+       "42  0.401104  0.440038  0.394245  0.408708  0.420681  0.442299  \n",
+       "43  0.161302  0.132285  0.096186  0.201539  0.198195  0.167421  \n",
+       "44  0.620384  0.637948  0.629167  0.640783  0.648596  0.611541  \n",
+       "45  0.715777  0.766721  0.720330  0.705289  0.712917  0.718007  \n",
+       "46  0.109012  0.082206  0.119163  0.092386  0.098278  0.134826  \n",
+       "47  0.130661  0.134397  0.164433  0.137992  0.151490  0.111528  \n",
+       "48  0.231120  0.146278  0.177644  0.214431  0.148552  0.203391  \n",
+       "49  0.208232  0.154013  0.217560  0.167469  0.114794  0.214311  \n",
+       "50  0.855393  0.854654  0.815397  0.848365  0.855520  0.900632  \n",
+       "51  0.657203  0.748811  0.702383  0.675559  0.747703  0.709482  \n",
+       "52  0.605271  0.694352  0.625864  0.584421  0.673791  0.628553  \n",
+       "53  0.288577  0.200789  0.275149  0.233916  0.192863  0.304376  \n",
+       "54  0.265764  0.248576  0.278403  0.269248  0.244609  0.286878  \n",
+       "55  0.695954  0.801029  0.754678  0.776418  0.751647  0.727862  \n",
+       "56  0.041037  0.082432  0.125600  0.037847  0.044367  0.092974  \n",
+       "57  0.382316  0.447347  0.433817  0.306990  0.424064  0.346655  \n",
+       "58  0.262740  0.206733  0.193760  0.209036  0.219223  0.228966  \n",
+       "59  0.582213  0.532573  0.501536  0.559082  0.570046  0.600431  \n",
+       "\n",
+       "[60 rows x 423 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_mix_train = pd.merge( left= df_dbeta,right=df_beta_train,left_on= 'ID',right_on='Unnamed: 0')\n",
+    "df_mix_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Unnamed: 0  cg03760483  cg00074348  cg04290171  cg00044665  cg14666310  \\\n",
+      "0             0.236414    0.466309    0.889514    0.266689    0.673555   \n",
+      "1             0.456963    0.457003    0.860040    0.332246    0.695180   \n",
+      "2             0.393205    0.442229    0.825669    0.269771    0.686634   \n",
+      "3             0.319442    0.460896    0.808767    0.315645    0.641230   \n",
+      "4             0.376546    0.526294    0.882251    0.234602    0.743104   \n",
+      "..                 ...         ...         ...         ...         ...   \n",
+      "413           0.376265    0.516885    0.819984    0.222106    0.679476   \n",
+      "414           0.200213    0.478009    0.803872    0.224438    0.632856   \n",
+      "415           0.213818    0.461991    0.918829    0.277983    0.651557   \n",
+      "416           0.223605    0.505650    0.854414    0.251191    0.654629   \n",
+      "417           0.390453    0.425387    0.911942    0.253250    0.694013   \n",
+      "\n",
+      "Unnamed: 0  cg07157107  cg02295216  cg19223467  cg23631930  cg12440062  ...  \\\n",
+      "0             0.267253    0.363497    0.553040    0.769073    0.486181  ...   \n",
+      "1             0.137766    0.260611    0.540875    0.786669    0.466767  ...   \n",
+      "2             0.212442    0.309377    0.408219    0.789469    0.658400  ...   \n",
+      "3             0.168600    0.350464    0.639611    0.712481    0.518216  ...   \n",
+      "4             0.206781    0.317099    0.540304    0.817953    0.593437  ...   \n",
+      "..                 ...         ...         ...         ...         ...  ...   \n",
+      "413           0.171719    0.351395    0.549210    0.820371    0.652818  ...   \n",
+      "414           0.162934    0.332551    0.517783    0.762424    0.559369  ...   \n",
+      "415           0.135706    0.167575    0.663231    0.798704    0.565027  ...   \n",
+      "416           0.190779    0.084872    0.433247    0.803269    0.574367  ...   \n",
+      "417           0.191123    0.345495    0.553600    0.778339    0.526302  ...   \n",
+      "\n",
+      "Unnamed: 0  cg20596724  cg16536739  cg04433322  cg02547394  cg12610471  \\\n",
+      "0             0.852856    0.701835    0.693354    0.216667    0.241770   \n",
+      "1             0.831449    0.644866    0.620378    0.343825    0.257214   \n",
+      "2             0.827896    0.695675    0.640691    0.321606    0.282535   \n",
+      "3             0.786247    0.631480    0.538186    0.272403    0.297399   \n",
+      "4             0.860701    0.690910    0.690076    0.195273    0.247937   \n",
+      "..                 ...         ...         ...         ...         ...   \n",
+      "413           0.854654    0.748811    0.694352    0.200789    0.248576   \n",
+      "414           0.815397    0.702383    0.625864    0.275149    0.278403   \n",
+      "415           0.848365    0.675559    0.584421    0.233916    0.269248   \n",
+      "416           0.855520    0.747703    0.673791    0.192863    0.244609   \n",
+      "417           0.900632    0.709482    0.628553    0.304376    0.286878   \n",
+      "\n",
+      "Unnamed: 0  cg06314202  cg06447795  cg14153654  cg24073122  cg23571857  \n",
+      "0             0.764468    0.044252    0.507465    0.234215    0.524199  \n",
+      "1             0.799973    0.029781    0.342007    0.245132    0.598047  \n",
+      "2             0.729717    0.069850    0.329841    0.254275    0.543003  \n",
+      "3             0.740498    0.139260    0.337737    0.257438    0.606595  \n",
+      "4             0.763586    0.094534    0.417720    0.192703    0.519143  \n",
+      "..                 ...         ...         ...         ...         ...  \n",
+      "413           0.801029    0.082432    0.447347    0.206733    0.532573  \n",
+      "414           0.754678    0.125600    0.433817    0.193760    0.501536  \n",
+      "415           0.776418    0.037847    0.306990    0.209036    0.559082  \n",
+      "416           0.751647    0.044367    0.424064    0.219223    0.570046  \n",
+      "417           0.727862    0.092974    0.346655    0.228966    0.600431  \n",
+      "\n",
+      "[418 rows x 60 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "\n",
+    "X_train = df_mix_train.drop(columns=[\"Unnamed: 0\",\"dbeta\",\"gene\",\"feature\",\"ID\"])\n",
+    "X_train = X_train.T\n",
+    "\n",
+    "X_train_normal_count = 218\n",
+    "\n",
+    "if (X_train_normal_count):\n",
+    "    y_train = [(0 if i < (X_train_normal_count) else 1) for i in range(len(X_train))]\n",
+    "    \n",
+    "X_train = X_train.T\n",
+    "\n",
+    "\n",
+    "X_train = pd.concat([ df_mix_train[\"Unnamed: 0\"], X_train], axis=1)\n",
+    "X_train.set_index(\"Unnamed: 0\", inplace=True)\n",
+    "\n",
+    "X_train = X_train.T\n",
+    "\n",
+    "X_train\n",
+    "print(X_train)\n",
+    "\n",
+    "# print(len(X_train))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Train accuracy (Random Forest): 0.7267\n",
+      "Test accuracy (Random Forest): 0.6482\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.model_selection import cross_validate\n",
+    "\n",
+    "# 初始化隨機森林模型\n",
+    "random_forest = RandomForestClassifier(random_state=42)\n",
+    "\n",
+    "# 手動調整隨機森林模型參數\n",
+    "random_forest.set_params(n_estimators=50, max_depth=4, min_samples_split=2, min_samples_leaf=40)\n",
+    "# 180/2/2/35\n",
+    "# 150/2/2/35\n",
+    "# \n",
+    "# 使用交叉驗證，並同時返回訓練集和測試集的準確率\n",
+    "cv_results = cross_validate(random_forest, X_train, y_train, cv=5, scoring='accuracy', return_train_score=True)\n",
+    "\n",
+    "# 輸出調整後的訓練集和測試集的交叉驗證平均準確率\n",
+    "print(f\"Train accuracy (Random Forest): {cv_results['train_score'].mean():.4f}\")\n",
+    "print(f\"Test accuracy (Random Forest): {cv_results['test_score'].mean():.4f}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: boruta in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (0.3)\n",
+      "Requirement already satisfied: numpy>=1.10.4 in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from boruta) (1.23.5)\n",
+      "Requirement already satisfied: scikit-learn>=0.17.1 in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from boruta) (1.3.2)\n",
+      "Requirement already satisfied: scipy>=0.17.0 in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from boruta) (1.10.1)\n",
+      "Requirement already satisfied: joblib>=1.1.1 in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-learn>=0.17.1->boruta) (1.3.2)\n",
+      "Requirement already satisfied: threadpoolctl>=2.0.0 in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-learn>=0.17.1->boruta) (3.2.0)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: Ignoring invalid distribution -uggingface-hub (c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages)\n",
+      "WARNING: Ignoring invalid distribution -uggingface-hub (c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages)\n",
+      "\n",
+      "[notice] A new release of pip is available: 24.0 -> 24.2\n",
+      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: scikit-optimize in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (0.10.2)Note: you may need to restart the kernel to use updated packages.\n",
+      "\n",
+      "Requirement already satisfied: joblib>=0.11 in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-optimize) (1.3.2)\n",
+      "Requirement already satisfied: pyaml>=16.9 in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-optimize) (24.7.0)\n",
+      "Requirement already satisfied: numpy>=1.20.3 in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-optimize) (1.23.5)\n",
+      "Requirement already satisfied: scipy>=1.1.0 in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-optimize) (1.10.1)\n",
+      "Requirement already satisfied: scikit-learn>=1.0.0 in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-optimize) (1.3.2)\n",
+      "Requirement already satisfied: packaging>=21.3 in c:\\users\\user\\appdata\\roaming\\python\\python310\\site-packages (from scikit-optimize) (21.3)\n",
+      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in c:\\users\\user\\appdata\\roaming\\python\\python310\\site-packages (from packaging>=21.3->scikit-optimize) (3.0.9)\n",
+      "Requirement already satisfied: PyYAML in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from pyaml>=16.9->scikit-optimize) (6.0)\n",
+      "Requirement already satisfied: threadpoolctl>=2.0.0 in c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-learn>=1.0.0->scikit-optimize) (3.2.0)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: Ignoring invalid distribution -uggingface-hub (c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages)\n",
+      "WARNING: Ignoring invalid distribution -uggingface-hub (c:\\users\\user\\appdata\\local\\programs\\python\\python310\\lib\\site-packages)\n",
+      "\n",
+      "[notice] A new release of pip is available: 24.0 -> 24.2\n",
+      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
+     ]
+    }
+   ],
+   "source": [
+    "%pip install boruta\n",
+    "%pip install scikit-optimize\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "最佳參數組合: [113.49612715   3.87267187   2.33139531  31.18069819   0.74531665]\n",
+      "最佳目標值 (最小化的F1損失): -0.6401367447029548\n"
+     ]
+    }
+   ],
+   "source": [
+    "from scipy.optimize import dual_annealing\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.model_selection import cross_val_score\n",
+    "import numpy as np\n",
+    "\n",
+    "# 定義目標函數，該函數通過5折交叉驗證來評估每個參數組合的性能\n",
+    "def objective(params):\n",
+    "    # 將參數轉換為整數\n",
+    "    n_estimators = int(params[0])\n",
+    "    max_depth = int(params[1])\n",
+    "    min_samples_split = int(params[2])\n",
+    "    min_samples_leaf = int(params[3])\n",
+    "    bootstrap = bool(params[4])\n",
+    "\n",
+    "    clf = RandomForestClassifier(\n",
+    "        n_estimators=n_estimators,\n",
+    "        max_depth=max_depth,\n",
+    "        min_samples_split=min_samples_split,\n",
+    "        min_samples_leaf=min_samples_leaf,\n",
+    "        bootstrap=bootstrap,\n",
+    "        n_jobs=-1,\n",
+    "        random_state=42\n",
+    "    )\n",
+    "\n",
+    "    # 使用5折交叉驗證來評估模型的F1分數，並返回負的平均分數（因為我們希望最小化）\n",
+    "    score = -cross_val_score(clf, X_train, y_train, cv=5, scoring='f1').mean()\n",
+    "    return score\n",
+    "\n",
+    "# 定義參數空間的範圍\n",
+    "param_bounds = [\n",
+    "    (100,200),   # n_estimators 的範圍，避免過多的樹\n",
+    "    (1, 7),       # max_depth 的範圍，進一步限制樹的最大深度\n",
+    "    (2, 5),      # min_samples_split 的範圍\n",
+    "    (35, 45),       # min_samples_leaf 的範圍\n",
+    "    (0, 1)        # bootstrap (0 表示 False，1 表示 True)\n",
+    "]\n",
+    "\n",
+    "# 使用 dual_annealing 進行模擬退火優化\n",
+    "result = dual_annealing(\n",
+    "    objective,     # 目標函數\n",
+    "    param_bounds,  # 參數空間\n",
+    "    maxiter=40,   # 模擬退火的最大迭代次數\n",
+    "    seed=42\n",
+    ")\n",
+    "\n",
+    "# 最佳結果\n",
+    "print(\"最佳參數組合:\", result.x)\n",
+    "print(\"最佳目標值 (最小化的F1損失):\", result.fun)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier(max_depth=3, min_samples_leaf=31, n_estimators=113,\n",
+       "                       n_jobs=-1, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestClassifier</label><div class=\"sk-toggleable__content\"><pre>RandomForestClassifier(max_depth=3, min_samples_leaf=31, n_estimators=113,\n",
+       "                       n_jobs=-1, random_state=42)</pre></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "RandomForestClassifier(max_depth=3, min_samples_leaf=31, n_estimators=113,\n",
+       "                       n_jobs=-1, random_state=42)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "best_rf = RandomForestClassifier(\n",
+    "    n_estimators=int(result.x[0]),  # 需要將浮點數轉換為整數\n",
+    "    max_depth=int(result.x[1]),\n",
+    "    min_samples_split=int(result.x[2]),\n",
+    "    min_samples_leaf=int(result.x[3]),\n",
+    "    bootstrap=bool(result.x[4]),  # 需要將0或1轉換為布爾值\n",
+    "    n_jobs=-1,\n",
+    "    random_state=42\n",
+    ")\n",
+    "\n",
+    "best_rf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "5-fold CV accuracy scores with best hyperparameters: [0.66666667 0.66666667 0.63013699 0.64197531 0.5952381 ]\n",
+      "f1: 0.6401367447029548\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 用最佳參數再次進行5折交叉驗證，這次用來評估最終結果\n",
+    "from sklearn.model_selection import cross_val_predict\n",
+    "\n",
+    "cv_scores = cross_val_score(best_rf, X_train, y_train, cv=5, scoring='f1')\n",
+    "predictions = cross_val_predict(best_rf, X_train, y_train, cv=5)\n",
+    "\n",
+    "# 打印五折交叉驗證結果和預測\n",
+    "print(f'5-fold CV accuracy scores with best hyperparameters: {cv_scores}')\n",
+    "print(f'f1: {np.mean(cv_scores)}')\n",
+    "# print(f'Predictions from 5-fold CV with best hyperparameters: {predictions}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Average train accuracy: 0.7553972651711502\n",
+      "Average test accuracy: 0.6624784853700516\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import cross_validate\n",
+    "# 使用 cross_validate 來同時獲取訓練和測試的準確率\n",
+    "cv_results = cross_validate(best_rf, X_train, y_train, cv=5, scoring='accuracy', return_train_score=True)\n",
+    "\n",
+    "# 取得訓練準確率和測試準確率\n",
+    "train_accuracy = cv_results['train_score']\n",
+    "test_accuracy = cv_results['test_score']\n",
+    "\n",
+    "# 分別輸出訓練準確率和測試準確率的平均值\n",
+    "print(\"Average train accuracy:\", train_accuracy.mean())\n",
+    "print(\"Average test accuracy:\", test_accuracy.mean())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Selected Features DataFrame:\n",
+      "Unnamed: 0  cg00074348  cg14666310  cg23631930  cg05724197  cg03003745  \\\n",
+      "0             0.466309    0.673555    0.769073    0.734243    0.769774   \n",
+      "1             0.457003    0.695180    0.786669    0.750670    0.754771   \n",
+      "2             0.442229    0.686634    0.789469    0.715007    0.750923   \n",
+      "3             0.460896    0.641230    0.712481    0.706211    0.707897   \n",
+      "4             0.526294    0.743104    0.817953    0.707622    0.803780   \n",
+      "\n",
+      "Unnamed: 0  cg00213123  cg20051772  cg13379236  cg05818394  cg00727675  ...  \\\n",
+      "0             0.252718    0.274093    0.573028    0.268786    0.846111  ...   \n",
+      "1             0.235994    0.153840    0.612531    0.219602    0.851785  ...   \n",
+      "2             0.283559    0.242470    0.601079    0.207522    0.807337  ...   \n",
+      "3             0.217079    0.201241    0.545201    0.205676    0.772323  ...   \n",
+      "4             0.254952    0.264579    0.595605    0.219931    0.896772  ...   \n",
+      "\n",
+      "Unnamed: 0  cg02329916  cg22746058  cg05506480  cg05884032  cg20596724  \\\n",
+      "0             0.697635    0.091921    0.178189    0.170969    0.852856   \n",
+      "1             0.804495    0.112488    0.157084    0.175475    0.831449   \n",
+      "2             0.774227    0.117563    0.094172    0.161222    0.827896   \n",
+      "3             0.735544    0.143644    0.140586    0.214139    0.786247   \n",
+      "4             0.766629    0.066142    0.110955    0.145597    0.860701   \n",
+      "\n",
+      "Unnamed: 0  cg04433322  cg02547394  cg12610471  cg14153654  cg24073122  \n",
+      "0             0.693354    0.216667    0.241770    0.507465    0.234215  \n",
+      "1             0.620378    0.343825    0.257214    0.342007    0.245132  \n",
+      "2             0.640691    0.321606    0.282535    0.329841    0.254275  \n",
+      "3             0.538186    0.272403    0.297399    0.337737    0.257438  \n",
+      "4             0.690076    0.195273    0.247937    0.417720    0.192703  \n",
+      "\n",
+      "[5 rows x 33 columns]\n",
+      "Selected Features: ['cg00074348', 'cg14666310', 'cg23631930', 'cg05724197', 'cg03003745', 'cg00213123', 'cg20051772', 'cg13379236', 'cg05818394', 'cg00727675', 'cg15059851', 'cg08375658', 'cg07925549', 'cg24296478', 'cg23792592', 'cg19157647', 'cg11201447', 'cg04927004', 'cg16570507', 'cg22500132', 'cg21298408', 'cg07552803', 'cg20248866', 'cg02329916', 'cg22746058', 'cg05506480', 'cg05884032', 'cg20596724', 'cg04433322', 'cg02547394', 'cg12610471', 'cg14153654', 'cg24073122']\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from boruta import BorutaPy\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "# 初始化隨機森林分類器\n",
+    "rf = best_rf\n",
+    "\n",
+    "# 初始化 Boruta\n",
+    "boruta = BorutaPy(rf, n_estimators='auto', verbose=0, random_state=42)\n",
+    "\n",
+    "# 執行特徵選擇\n",
+    "# X_train.to_csv(\"t.csv\")\n",
+    "# print(X_train.values)\n",
+    "\n",
+    "y_train = np.array(y_train)\n",
+    "boruta.fit(X_train.values, y_train)\n",
+    "\n",
+    "# 獲取選中的特徵\n",
+    "X_selected = X_train.iloc[:, boruta.support_]\n",
+    "\n",
+    "# 打印選中的特徵\n",
+    "print(\"Selected Features DataFrame:\")\n",
+    "print(X_selected.head())\n",
+    "\n",
+    "selected_features = X_train.columns[boruta.support_]\n",
+    "print(\"Selected Features: %s\" % list(selected_features))\n",
+    "\n",
+    "# 獲取特徵的排名\n",
+    "ranking = boruta.ranking_[boruta.support_]\n",
+    "\n",
+    "# 將特徵及其排名組成 DataFrame\n",
+    "features_df = pd.DataFrame({\n",
+    "    'boruta_feature': selected_features,\n",
+    "})\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Sorted Selected Features with Rankings:\n",
+      "   boruta_feature\n",
+      "0      cg00074348\n",
+      "1      cg14666310\n",
+      "2      cg23631930\n",
+      "3      cg05724197\n",
+      "4      cg03003745\n",
+      "5      cg00213123\n",
+      "6      cg20051772\n",
+      "7      cg13379236\n",
+      "8      cg05818394\n",
+      "9      cg00727675\n",
+      "10     cg15059851\n",
+      "11     cg08375658\n",
+      "12     cg07925549\n",
+      "13     cg24296478\n",
+      "14     cg23792592\n",
+      "15     cg19157647\n",
+      "16     cg11201447\n",
+      "17     cg04927004\n",
+      "18     cg16570507\n",
+      "19     cg22500132\n",
+      "20     cg21298408\n",
+      "21     cg07552803\n",
+      "22     cg20248866\n",
+      "23     cg02329916\n",
+      "24     cg22746058\n",
+      "25     cg05506480\n",
+      "26     cg05884032\n",
+      "27     cg20596724\n",
+      "28     cg04433322\n",
+      "29     cg02547394\n",
+      "30     cg12610471\n",
+      "31     cg14153654\n",
+      "32     cg24073122\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 打印排序後的特徵名稱和排名\n",
+    "print(\"Sorted Selected Features with Rankings:\")\n",
+    "print(features_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RFECV Selected Features: ['cg00074348', 'cg14666310', 'cg23631930', 'cg12440062', 'cg05724197', 'cg03003745', 'cg00213123', 'cg20051772', 'cg13379236', 'cg13816423', 'cg19772011', 'cg05818394', 'cg00727675', 'cg15059851', 'cg08375658', 'cg07925549', 'cg24296478', 'cg23792592', 'cg19157647', 'cg11201447', 'cg04927004', 'cg16570507', 'cg22500132', 'cg21298408', 'cg07552803', 'cg20248866', 'cg02329916', 'cg22746058', 'cg05506480', 'cg05884032', 'cg20596724', 'cg04433322', 'cg02547394', 'cg12610471', 'cg06314202', 'cg14153654']\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from boruta import BorutaPy\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.feature_selection import RFECV\n",
+    "from sklearn.metrics import classification_report,make_scorer,f1_score\n",
+    "\n",
+    "\n",
+    "rf = best_rf\n",
+    "\n",
+    "scoror = make_scorer(f1_score, average='macro')\n",
+    "\n",
+    "rfecv = RFECV(estimator=rf, step=1, cv=5, scoring=scoror)\n",
+    "# rfecv = RFECV(estimator=rf, step=1, cv=5, scoring='accuracy')\n",
+    "rfecv.fit(X_train, y_train)\n",
+    "\n",
+    "# 獲取 RFECV 選中的特徵\n",
+    "rfecv_features = X_train.columns[rfecv.support_]\n",
+    "print(\"RFECV Selected Features: %s\" % list(rfecv_features))\n",
+    "\n",
+    "rfecv_features_df=pd.DataFrame({\n",
+    "    'rfecv_feature': rfecv_features,\n",
+    "})\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "   rfecv_feature\n",
+      "0     cg00074348\n",
+      "1     cg14666310\n",
+      "2     cg23631930\n",
+      "3     cg12440062\n",
+      "4     cg05724197\n",
+      "5     cg03003745\n",
+      "6     cg00213123\n",
+      "7     cg20051772\n",
+      "8     cg13379236\n",
+      "9     cg13816423\n",
+      "10    cg19772011\n",
+      "11    cg05818394\n",
+      "12    cg00727675\n",
+      "13    cg15059851\n",
+      "14    cg08375658\n",
+      "15    cg07925549\n",
+      "16    cg24296478\n",
+      "17    cg23792592\n",
+      "18    cg19157647\n",
+      "19    cg11201447\n",
+      "20    cg04927004\n",
+      "21    cg16570507\n",
+      "22    cg22500132\n",
+      "23    cg21298408\n",
+      "24    cg07552803\n",
+      "25    cg20248866\n",
+      "26    cg02329916\n",
+      "27    cg22746058\n",
+      "28    cg05506480\n",
+      "29    cg05884032\n",
+      "30    cg20596724\n",
+      "31    cg04433322\n",
+      "32    cg02547394\n",
+      "33    cg12610471\n",
+      "34    cg06314202\n",
+      "35    cg14153654\n",
+      "36\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(rfecv_features_df)\n",
+    "print(len(rfecv_features))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "   boruta_feature rfecv_feature\n",
+      "0      cg00074348    cg00074348\n",
+      "1      cg14666310    cg14666310\n",
+      "2      cg23631930    cg23631930\n",
+      "3      cg05724197    cg05724197\n",
+      "4      cg03003745    cg03003745\n",
+      "5      cg00213123    cg00213123\n",
+      "6      cg20051772    cg20051772\n",
+      "7      cg13379236    cg13379236\n",
+      "8      cg05818394    cg05818394\n",
+      "9      cg00727675    cg00727675\n",
+      "10     cg15059851    cg15059851\n",
+      "11     cg08375658    cg08375658\n",
+      "12     cg07925549    cg07925549\n",
+      "13     cg24296478    cg24296478\n",
+      "14     cg23792592    cg23792592\n",
+      "15     cg19157647    cg19157647\n",
+      "16     cg11201447    cg11201447\n",
+      "17     cg04927004    cg04927004\n",
+      "18     cg16570507    cg16570507\n",
+      "19     cg22500132    cg22500132\n",
+      "20     cg21298408    cg21298408\n",
+      "21     cg07552803    cg07552803\n",
+      "22     cg20248866    cg20248866\n",
+      "23     cg02329916    cg02329916\n",
+      "24     cg22746058    cg22746058\n",
+      "25     cg05506480    cg05506480\n",
+      "26     cg05884032    cg05884032\n",
+      "27     cg20596724    cg20596724\n",
+      "28     cg04433322    cg04433322\n",
+      "29     cg02547394    cg02547394\n",
+      "30     cg12610471    cg12610471\n",
+      "31     cg14153654    cg14153654\n",
+      "32     cg24073122           NaN\n",
+      "33            NaN    cg12440062\n",
+      "34            NaN    cg13816423\n",
+      "35            NaN    cg19772011\n",
+      "36            NaN    cg06314202\n",
+      "       feature\n",
+      "0   cg00074348\n",
+      "1   cg14666310\n",
+      "2   cg23631930\n",
+      "3   cg05724197\n",
+      "4   cg03003745\n",
+      "5   cg00213123\n",
+      "6   cg20051772\n",
+      "7   cg13379236\n",
+      "8   cg05818394\n",
+      "9   cg00727675\n",
+      "10  cg15059851\n",
+      "11  cg08375658\n",
+      "12  cg07925549\n",
+      "13  cg24296478\n",
+      "14  cg23792592\n",
+      "15  cg19157647\n",
+      "16  cg11201447\n",
+      "17  cg04927004\n",
+      "18  cg16570507\n",
+      "19  cg22500132\n",
+      "20  cg21298408\n",
+      "21  cg07552803\n",
+      "22  cg20248866\n",
+      "23  cg02329916\n",
+      "24  cg22746058\n",
+      "25  cg05506480\n",
+      "26  cg05884032\n",
+      "27  cg20596724\n",
+      "28  cg04433322\n",
+      "29  cg02547394\n",
+      "30  cg12610471\n",
+      "31  cg14153654\n",
+      "32         NaN\n",
+      "33         NaN\n",
+      "34         NaN\n",
+      "35         NaN\n"
+     ]
+    }
+   ],
+   "source": [
+    "all_features_df = pd.merge(left=features_df,right=rfecv_features_df,left_on=\"boruta_feature\",right_on='rfecv_feature', how='outer')\n",
+    "\n",
+    "print(all_features_df)\n",
+    "\n",
+    "inner = pd.merge(left=all_features_df,right=all_features_df,left_on=['boruta_feature'],right_on=['rfecv_feature'])\n",
+    "inner = inner[['boruta_feature_x']].rename(columns={'boruta_feature_x': 'feature'})\n",
+    "\n",
+    "print(inner)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gene</th>\n",
+       "      <th>cluster</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>ALOX12</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>APLNR</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>CD46</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>CDH5</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>CEACAM5</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>CHRNA6</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>CKLF</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>CLEC9A</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>CMTM5</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>CRISP2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>CRTC1</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>CSMD1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>CX3CL1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>CXCL17</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>CYP1A1</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>DGKA</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>EGF</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>FOXP4</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>GJB5</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>GLP1R</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>GNA13</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>HIPK3</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>HMGB1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>HOXA3</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>IL32</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>IVL</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>KCNE3</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>KLK12</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>KRT75</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>LCOR</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>MIR1-1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>MIR1180</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>MIR124-3</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>MIR134</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>MIR141</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>MIR346</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>MIR493</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>MUC1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>NAT1</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>NEFM</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>PANX3</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>PCYT2</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>PDCD1LG2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>PGC</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>PRSS1</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>PTF1A</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>RAB6B</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>RING1</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>SALL3</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>SDR9C7</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>SFRP5</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>SLC4A1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>SOX1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>SPAG6</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>54</th>\n",
+       "      <td>SSTR5</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>55</th>\n",
+       "      <td>TGM2</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56</th>\n",
+       "      <td>TNFRSF9</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57</th>\n",
+       "      <td>TP73</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58</th>\n",
+       "      <td>XAF1</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        gene  cluster\n",
+       "0     ALOX12        4\n",
+       "1      APLNR        2\n",
+       "2       CD46        2\n",
+       "3       CDH5        2\n",
+       "4    CEACAM5        2\n",
+       "5     CHRNA6        2\n",
+       "6       CKLF        2\n",
+       "7     CLEC9A        2\n",
+       "8      CMTM5        2\n",
+       "9     CRISP2        2\n",
+       "10     CRTC1        4\n",
+       "11     CSMD1        2\n",
+       "12    CX3CL1        2\n",
+       "13    CXCL17        2\n",
+       "14    CYP1A1        4\n",
+       "15      DGKA        4\n",
+       "16       EGF        2\n",
+       "17     FOXP4        3\n",
+       "18      GJB5        2\n",
+       "19     GLP1R        2\n",
+       "20     GNA13        2\n",
+       "21     HIPK3        4\n",
+       "22     HMGB1        2\n",
+       "23     HOXA3        3\n",
+       "24      IL32        2\n",
+       "25       IVL        4\n",
+       "26     KCNE3        2\n",
+       "27     KLK12        4\n",
+       "28     KRT75        4\n",
+       "29      LCOR        3\n",
+       "30    MIR1-1        1\n",
+       "31   MIR1180        1\n",
+       "32  MIR124-3        1\n",
+       "33    MIR134        1\n",
+       "34    MIR141        1\n",
+       "35    MIR346        1\n",
+       "36    MIR493        1\n",
+       "37      MUC1        3\n",
+       "38      NAT1        4\n",
+       "39      NEFM        4\n",
+       "40     PANX3        2\n",
+       "41     PCYT2        4\n",
+       "42  PDCD1LG2        2\n",
+       "43       PGC        4\n",
+       "44     PRSS1        4\n",
+       "45     PTF1A        3\n",
+       "46     RAB6B        4\n",
+       "47     RING1        4\n",
+       "48     SALL3        3\n",
+       "49    SDR9C7        4\n",
+       "50     SFRP5        2\n",
+       "51    SLC4A1        2\n",
+       "52      SOX1        3\n",
+       "53     SPAG6        4\n",
+       "54     SSTR5        2\n",
+       "55      TGM2        4\n",
+       "56   TNFRSF9        2\n",
+       "57      TP73        3\n",
+       "58      XAF1        4"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_cluster = pd.read_csv(\"result/GSE243529_xzh/dbeta_GSE243529_TSS_0.15_consensus.csv\")\n",
+    "df_cluster\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "        gene  cluster          ID     dbeta  feature\n",
+      "0     ALOX12        4  cg03760483  0.157175   TSS200\n",
+      "1      APLNR        2  cg00074348 -0.187434  TSS1500\n",
+      "2       CD46        2  cg04290171 -0.201098  TSS1500\n",
+      "3       CDH5        2  cg00044665  0.206568   TSS200\n",
+      "4    CEACAM5        2  cg14666310 -0.210341  TSS1500\n",
+      "5     CHRNA6        2  cg07157107 -0.242190   TSS200\n",
+      "6       CKLF        2  cg02295216  0.172590  TSS1500\n",
+      "7     CLEC9A        2  cg19223467 -0.152339   TSS200\n",
+      "8      CMTM5        2  cg23631930  0.172075   TSS200\n",
+      "9     CRISP2        2  cg12440062  0.200273   TSS200\n",
+      "10     CRTC1        4  cg21290814 -0.160943  TSS1500\n",
+      "11     CSMD1        2  cg01136458 -0.183525  TSS1500\n",
+      "12    CX3CL1        2  cg05724197  0.198136  TSS1500\n",
+      "13    CXCL17        2  cg03003745 -0.238256  TSS1500\n",
+      "14    CYP1A1        4  cg00213123  0.195047  TSS1500\n",
+      "15      DGKA        4  cg20051772 -0.186669  TSS1500\n",
+      "16       EGF        2  cg13379236 -0.151026  TSS1500\n",
+      "17     FOXP4        3  cg13816423 -0.206186  TSS1500\n",
+      "18      GJB5        2  cg07014349  0.162041   TSS200\n",
+      "19     GLP1R        2  cg19772011 -0.174030  TSS1500\n",
+      "20     GNA13        2  cg17413194  0.174816  TSS1500\n",
+      "21     HIPK3        4  cg04225088  0.150001  TSS1500\n",
+      "22     HMGB1        2  cg05818394 -0.291705  TSS1500\n",
+      "23     HOXA3        3  cg00727675 -0.182567  TSS1500\n",
+      "24      IL32        2  cg00239353  0.230341  TSS1500\n",
+      "25       IVL        4  cg15059851 -0.208371  TSS1500\n",
+      "26     KCNE3        2  cg11775521  0.263576   TSS200\n",
+      "27     KLK12        4  cg08375658 -0.150620  TSS1500\n",
+      "28     KRT75        4  cg07925549 -0.170578  TSS1500\n",
+      "29      LCOR        3  cg24296478 -0.157586  TSS1500\n",
+      "30    MIR1-1        1  cg23792592 -0.180821  TSS1500\n",
+      "31   MIR1180        1  cg19157647  0.157648   TSS200\n",
+      "32  MIR124-3        1  cg04927004  0.177844  TSS1500\n",
+      "33    MIR134        1  cg10734581 -0.266630  TSS1500\n",
+      "34    MIR141        1  cg24702147 -0.157450  TSS1500\n",
+      "35    MIR346        1  cg16570507 -0.179525   TSS200\n",
+      "36    MIR493        1  cg02577745 -0.163426  TSS1500\n",
+      "37      MUC1        3  cg22500132 -0.282771   TSS200\n",
+      "38      NAT1        4  cg21298408 -0.159201   TSS200\n",
+      "39      NEFM        4  cg07552803  0.227250  TSS1500\n",
+      "40     PANX3        2  cg08317412 -0.169833  TSS1500\n",
+      "41     PCYT2        4  cg20248866  0.154787  TSS1500\n",
+      "42  PDCD1LG2        2  cg07211259  0.152846   TSS200\n",
+      "43       PGC        4  cg12871376 -0.152930  TSS1500\n",
+      "44     PRSS1        4  cg02329916 -0.206755   TSS200\n",
+      "45     PTF1A        3  cg22746058  0.189984  TSS1500\n",
+      "46     RAB6B        4  cg05506480 -0.195065  TSS1500\n",
+      "47     RING1        4  cg26106778  0.186264  TSS1500\n",
+      "48     SALL3        3  cg05884032  0.151857   TSS200\n",
+      "49    SDR9C7        4  cg20596724 -0.198220  TSS1500\n",
+      "50     SFRP5        2  cg16536739 -0.152947  TSS1500\n",
+      "51    SLC4A1        2  cg04433322 -0.211638  TSS1500\n",
+      "52      SOX1        3  cg02547394  0.228038   TSS200\n",
+      "53     SPAG6        4  cg12610471  0.281363   TSS200\n",
+      "54     SSTR5        2  cg06314202 -0.208831  TSS1500\n",
+      "55      TGM2        4  cg06447795 -0.193115  TSS1500\n",
+      "56   TNFRSF9        2  cg14153654 -0.195903   TSS200\n",
+      "57      TP73        3  cg24073122  0.209996  TSS1500\n",
+      "58      XAF1        4  cg23571857  0.216849  TSS1500\n",
+      "        gene  cluster          ID     dbeta feature_x\n",
+      "0      APLNR        2  cg00074348 -0.187434   TSS1500\n",
+      "1    CEACAM5        2  cg14666310 -0.210341   TSS1500\n",
+      "2      CMTM5        2  cg23631930  0.172075    TSS200\n",
+      "3     CX3CL1        2  cg05724197  0.198136   TSS1500\n",
+      "4     CXCL17        2  cg03003745 -0.238256   TSS1500\n",
+      "5     CYP1A1        4  cg00213123  0.195047   TSS1500\n",
+      "6       DGKA        4  cg20051772 -0.186669   TSS1500\n",
+      "7        EGF        2  cg13379236 -0.151026   TSS1500\n",
+      "8      HMGB1        2  cg05818394 -0.291705   TSS1500\n",
+      "9      HOXA3        3  cg00727675 -0.182567   TSS1500\n",
+      "10       IVL        4  cg15059851 -0.208371   TSS1500\n",
+      "11     KLK12        4  cg08375658 -0.150620   TSS1500\n",
+      "12     KRT75        4  cg07925549 -0.170578   TSS1500\n",
+      "13      LCOR        3  cg24296478 -0.157586   TSS1500\n",
+      "14    MIR1-1        1  cg23792592 -0.180821   TSS1500\n",
+      "15   MIR1180        1  cg19157647  0.157648    TSS200\n",
+      "16  MIR124-3        1  cg04927004  0.177844   TSS1500\n",
+      "17    MIR346        1  cg16570507 -0.179525    TSS200\n",
+      "18      MUC1        3  cg22500132 -0.282771    TSS200\n",
+      "19      NAT1        4  cg21298408 -0.159201    TSS200\n",
+      "20      NEFM        4  cg07552803  0.227250   TSS1500\n",
+      "21     PCYT2        4  cg20248866  0.154787   TSS1500\n",
+      "22     PRSS1        4  cg02329916 -0.206755    TSS200\n",
+      "23     PTF1A        3  cg22746058  0.189984   TSS1500\n",
+      "24     RAB6B        4  cg05506480 -0.195065   TSS1500\n",
+      "25     SALL3        3  cg05884032  0.151857    TSS200\n",
+      "26    SDR9C7        4  cg20596724 -0.198220   TSS1500\n",
+      "27    SLC4A1        2  cg04433322 -0.211638   TSS1500\n",
+      "28      SOX1        3  cg02547394  0.228038    TSS200\n",
+      "29     SPAG6        4  cg12610471  0.281363    TSS200\n",
+      "30   TNFRSF9        2  cg14153654 -0.195903    TSS200\n",
+      "        gene  cluster          ID     dbeta feature_x\n",
+      "2      CMTM5        2  cg23631930  0.172075    TSS200\n",
+      "3     CX3CL1        2  cg05724197  0.198136   TSS1500\n",
+      "5     CYP1A1        4  cg00213123  0.195047   TSS1500\n",
+      "15   MIR1180        1  cg19157647  0.157648    TSS200\n",
+      "16  MIR124-3        1  cg04927004  0.177844   TSS1500\n",
+      "20      NEFM        4  cg07552803  0.227250   TSS1500\n",
+      "21     PCYT2        4  cg20248866  0.154787   TSS1500\n",
+      "23     PTF1A        3  cg22746058  0.189984   TSS1500\n",
+      "25     SALL3        3  cg05884032  0.151857    TSS200\n",
+      "28      SOX1        3  cg02547394  0.228038    TSS200\n",
+      "29     SPAG6        4  cg12610471  0.281363    TSS200\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_cluster_dbeta = pd.merge(left= df_cluster,right =df_dbeta,left_on ='gene',right_on='gene' )\n",
+    "# df_cluster_dbeta = df_cluster_dbeta.drop(columns=['gene'])\n",
+    "print(df_cluster_dbeta)\n",
+    "\n",
+    "\n",
+    "df_cluster_select = pd.merge(left= df_cluster_dbeta,right=inner,left_on ='ID',right_on='feature' )\n",
+    "df_cluster_select=df_cluster_select.drop(columns=['feature_y'])\n",
+    "print(df_cluster_select)\n",
+    "df_cluster_select.to_csv('result/GSE243529_xzh/boruta_consensus_clustering_result_xzh_reuse.csv',index=False)\n",
+    "# df_cluster_select.to_csv('result/xzh_GSE243529/boruta_average_clustering_result_xzh.csv',index=False)\n",
+    "\n",
+    "filtered_df = df_cluster_select[df_cluster_select[\"dbeta\"] > 0]\n",
+    "# 印出篩選後的 DataFrame\n",
+    "print(filtered_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 186,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['cg23792592', 'cg00074348', 'cg00727675', 'cg00213123']\n",
+      "4\n",
+      "cg23792592,cg00074348,cg00727675,cg00213123\n",
+      "cg23792592,cg00074348,cg00727675,cg20051772\n",
+      "cg23792592,cg00074348,cg00727675,cg15059851\n",
+      "cg23792592,cg00074348,cg00727675,cg08375658\n",
+      "cg23792592,cg00074348,cg00727675,cg07925549\n",
+      "cg23792592,cg00074348,cg00727675,cg21298408\n",
+      "cg23792592,cg00074348,cg00727675,cg07552803\n",
+      "cg23792592,cg00074348,cg00727675,cg20248866\n",
+      "cg23792592,cg00074348,cg00727675,cg02329916\n",
+      "cg23792592,cg00074348,cg00727675,cg20596724\n",
+      "cg23792592,cg00074348,cg00727675,cg12610471\n",
+      "cg23792592,cg00074348,cg22500132,cg00213123\n",
+      "cg23792592,cg00074348,cg22500132,cg20051772\n",
+      "cg23792592,cg00074348,cg22500132,cg15059851\n",
+      "cg23792592,cg00074348,cg22500132,cg08375658\n",
+      "cg23792592,cg00074348,cg22500132,cg07925549\n",
+      "cg23792592,cg00074348,cg22500132,cg21298408\n",
+      "cg23792592,cg00074348,cg22500132,cg07552803\n",
+      "cg23792592,cg00074348,cg22500132,cg20248866\n",
+      "cg23792592,cg00074348,cg22500132,cg02329916\n",
+      "cg23792592,cg00074348,cg22500132,cg20596724\n",
+      "cg23792592,cg00074348,cg22500132,cg12610471\n",
+      "cg23792592,cg00074348,cg22746058,cg00213123\n",
+      "cg23792592,cg00074348,cg22746058,cg20051772\n",
+      "cg23792592,cg00074348,cg22746058,cg15059851\n",
+      "cg23792592,cg00074348,cg22746058,cg08375658\n",
+      "cg23792592,cg00074348,cg22746058,cg07925549\n",
+      "cg23792592,cg00074348,cg22746058,cg21298408\n",
+      "cg23792592,cg00074348,cg22746058,cg07552803\n",
+      "cg23792592,cg00074348,cg22746058,cg20248866\n",
+      "cg23792592,cg00074348,cg22746058,cg02329916\n",
+      "cg23792592,cg00074348,cg22746058,cg20596724\n",
+      "cg23792592,cg00074348,cg22746058,cg12610471\n",
+      "cg23792592,cg00074348,cg05884032,cg00213123\n",
+      "cg23792592,cg00074348,cg05884032,cg20051772\n",
+      "cg23792592,cg00074348,cg05884032,cg15059851\n",
+      "cg23792592,cg00074348,cg05884032,cg08375658\n",
+      "cg23792592,cg00074348,cg05884032,cg07925549\n",
+      "cg23792592,cg00074348,cg05884032,cg21298408\n",
+      "cg23792592,cg00074348,cg05884032,cg07552803\n",
+      "cg23792592,cg00074348,cg05884032,cg20248866\n",
+      "cg23792592,cg00074348,cg05884032,cg02329916\n",
+      "cg23792592,cg00074348,cg05884032,cg20596724\n",
+      "cg23792592,cg00074348,cg05884032,cg12610471\n",
+      "cg23792592,cg00074348,cg02547394,cg00213123\n",
+      "cg23792592,cg00074348,cg02547394,cg20051772\n",
+      "cg23792592,cg00074348,cg02547394,cg15059851\n",
+      "cg23792592,cg00074348,cg02547394,cg08375658\n",
+      "cg23792592,cg00074348,cg02547394,cg07925549\n",
+      "cg23792592,cg00074348,cg02547394,cg21298408\n",
+      "cg23792592,cg00074348,cg02547394,cg07552803\n",
+      "cg23792592,cg00074348,cg02547394,cg20248866\n",
+      "cg23792592,cg00074348,cg02547394,cg02329916\n",
+      "cg23792592,cg00074348,cg02547394,cg20596724\n",
+      "cg23792592,cg00074348,cg02547394,cg12610471\n",
+      "cg23792592,cg00074348,cg24073122,cg00213123\n",
+      "cg23792592,cg00074348,cg24073122,cg20051772\n",
+      "cg23792592,cg00074348,cg24073122,cg15059851\n",
+      "cg23792592,cg00074348,cg24073122,cg08375658\n",
+      "cg23792592,cg00074348,cg24073122,cg07925549\n",
+      "cg23792592,cg00074348,cg24073122,cg21298408\n",
+      "cg23792592,cg00074348,cg24073122,cg07552803\n",
+      "cg23792592,cg00074348,cg24073122,cg20248866\n",
+      "cg23792592,cg00074348,cg24073122,cg02329916\n",
+      "cg23792592,cg00074348,cg24073122,cg20596724\n",
+      "cg23792592,cg00074348,cg24073122,cg12610471\n",
+      "cg23792592,cg14666310,cg00727675,cg00213123\n",
+      "cg23792592,cg14666310,cg00727675,cg20051772\n",
+      "cg23792592,cg14666310,cg00727675,cg15059851\n",
+      "cg23792592,cg14666310,cg00727675,cg08375658\n",
+      "cg23792592,cg14666310,cg00727675,cg07925549\n",
+      "cg23792592,cg14666310,cg00727675,cg21298408\n",
+      "cg23792592,cg14666310,cg00727675,cg07552803\n",
+      "cg23792592,cg14666310,cg00727675,cg20248866\n",
+      "cg23792592,cg14666310,cg00727675,cg02329916\n",
+      "cg23792592,cg14666310,cg00727675,cg20596724\n",
+      "cg23792592,cg14666310,cg00727675,cg12610471\n",
+      "cg23792592,cg14666310,cg22500132,cg00213123\n",
+      "cg23792592,cg14666310,cg22500132,cg20051772\n",
+      "cg23792592,cg14666310,cg22500132,cg15059851\n",
+      "cg23792592,cg14666310,cg22500132,cg08375658\n",
+      "cg23792592,cg14666310,cg22500132,cg07925549\n",
+      "cg23792592,cg14666310,cg22500132,cg21298408\n",
+      "cg23792592,cg14666310,cg22500132,cg07552803\n",
+      "cg23792592,cg14666310,cg22500132,cg20248866\n",
+      "cg23792592,cg14666310,cg22500132,cg02329916\n",
+      "cg23792592,cg14666310,cg22500132,cg20596724\n",
+      "cg23792592,cg14666310,cg22500132,cg12610471\n",
+      "cg23792592,cg14666310,cg22746058,cg00213123\n",
+      "cg23792592,cg14666310,cg22746058,cg20051772\n",
+      "cg23792592,cg14666310,cg22746058,cg15059851\n",
+      "cg23792592,cg14666310,cg22746058,cg08375658\n",
+      "cg23792592,cg14666310,cg22746058,cg07925549\n",
+      "cg23792592,cg14666310,cg22746058,cg21298408\n",
+      "cg23792592,cg14666310,cg22746058,cg07552803\n",
+      "cg23792592,cg14666310,cg22746058,cg20248866\n",
+      "cg23792592,cg14666310,cg22746058,cg02329916\n",
+      "cg23792592,cg14666310,cg22746058,cg20596724\n",
+      "cg23792592,cg14666310,cg22746058,cg12610471\n",
+      "cg23792592,cg14666310,cg05884032,cg00213123\n",
+      "cg23792592,cg14666310,cg05884032,cg20051772\n",
+      "cg23792592,cg14666310,cg05884032,cg15059851\n",
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+      "cg16570507,cg05818394,cg22500132,cg21298408\n",
+      "cg16570507,cg05818394,cg22500132,cg07552803\n",
+      "cg16570507,cg05818394,cg22500132,cg20248866\n",
+      "cg16570507,cg05818394,cg22500132,cg02329916\n",
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+      "cg16570507,cg05818394,cg22500132,cg12610471\n",
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+      "cg16570507,cg05818394,cg22746058,cg20051772\n",
+      "cg16570507,cg05818394,cg22746058,cg15059851\n",
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+      "cg16570507,cg05818394,cg22746058,cg07925549\n",
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+      "cg16570507,cg05818394,cg22746058,cg20596724\n",
+      "cg16570507,cg05818394,cg22746058,cg12610471\n",
+      "cg16570507,cg05818394,cg05884032,cg00213123\n",
+      "cg16570507,cg05818394,cg05884032,cg20051772\n",
+      "cg16570507,cg05818394,cg05884032,cg15059851\n",
+      "cg16570507,cg05818394,cg05884032,cg08375658\n",
+      "cg16570507,cg05818394,cg05884032,cg07925549\n",
+      "cg16570507,cg05818394,cg05884032,cg21298408\n",
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+      "cg16570507,cg05818394,cg05884032,cg20248866\n",
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+      "cg16570507,cg05818394,cg05884032,cg12610471\n",
+      "cg16570507,cg05818394,cg02547394,cg00213123\n",
+      "cg16570507,cg05818394,cg02547394,cg20051772\n",
+      "cg16570507,cg05818394,cg02547394,cg15059851\n",
+      "cg16570507,cg05818394,cg02547394,cg08375658\n",
+      "cg16570507,cg05818394,cg02547394,cg07925549\n",
+      "cg16570507,cg05818394,cg02547394,cg21298408\n",
+      "cg16570507,cg05818394,cg02547394,cg07552803\n",
+      "cg16570507,cg05818394,cg02547394,cg20248866\n",
+      "cg16570507,cg05818394,cg02547394,cg02329916\n",
+      "cg16570507,cg05818394,cg02547394,cg20596724\n",
+      "cg16570507,cg05818394,cg02547394,cg12610471\n",
+      "cg16570507,cg05818394,cg24073122,cg00213123\n",
+      "cg16570507,cg05818394,cg24073122,cg20051772\n",
+      "cg16570507,cg05818394,cg24073122,cg15059851\n",
+      "cg16570507,cg05818394,cg24073122,cg08375658\n",
+      "cg16570507,cg05818394,cg24073122,cg07925549\n",
+      "cg16570507,cg05818394,cg24073122,cg21298408\n",
+      "cg16570507,cg05818394,cg24073122,cg07552803\n",
+      "cg16570507,cg05818394,cg24073122,cg20248866\n",
+      "cg16570507,cg05818394,cg24073122,cg02329916\n",
+      "cg16570507,cg05818394,cg24073122,cg20596724\n",
+      "cg16570507,cg05818394,cg24073122,cg12610471\n",
+      "cg16570507,cg04433322,cg00727675,cg00213123\n",
+      "cg16570507,cg04433322,cg00727675,cg20051772\n",
+      "cg16570507,cg04433322,cg00727675,cg15059851\n",
+      "cg16570507,cg04433322,cg00727675,cg08375658\n",
+      "cg16570507,cg04433322,cg00727675,cg07925549\n",
+      "cg16570507,cg04433322,cg00727675,cg21298408\n",
+      "cg16570507,cg04433322,cg00727675,cg07552803\n",
+      "cg16570507,cg04433322,cg00727675,cg20248866\n",
+      "cg16570507,cg04433322,cg00727675,cg02329916\n",
+      "cg16570507,cg04433322,cg00727675,cg20596724\n",
+      "cg16570507,cg04433322,cg00727675,cg12610471\n",
+      "cg16570507,cg04433322,cg22500132,cg00213123\n",
+      "cg16570507,cg04433322,cg22500132,cg20051772\n",
+      "cg16570507,cg04433322,cg22500132,cg15059851\n",
+      "cg16570507,cg04433322,cg22500132,cg08375658\n",
+      "cg16570507,cg04433322,cg22500132,cg07925549\n",
+      "cg16570507,cg04433322,cg22500132,cg21298408\n",
+      "cg16570507,cg04433322,cg22500132,cg07552803\n",
+      "cg16570507,cg04433322,cg22500132,cg20248866\n",
+      "cg16570507,cg04433322,cg22500132,cg02329916\n",
+      "cg16570507,cg04433322,cg22500132,cg20596724\n",
+      "cg16570507,cg04433322,cg22500132,cg12610471\n",
+      "cg16570507,cg04433322,cg22746058,cg00213123\n",
+      "cg16570507,cg04433322,cg22746058,cg20051772\n",
+      "cg16570507,cg04433322,cg22746058,cg15059851\n",
+      "cg16570507,cg04433322,cg22746058,cg08375658\n",
+      "cg16570507,cg04433322,cg22746058,cg07925549\n",
+      "cg16570507,cg04433322,cg22746058,cg21298408\n",
+      "cg16570507,cg04433322,cg22746058,cg07552803\n",
+      "cg16570507,cg04433322,cg22746058,cg20248866\n",
+      "cg16570507,cg04433322,cg22746058,cg02329916\n",
+      "cg16570507,cg04433322,cg22746058,cg20596724\n",
+      "cg16570507,cg04433322,cg22746058,cg12610471\n",
+      "cg16570507,cg04433322,cg05884032,cg00213123\n",
+      "cg16570507,cg04433322,cg05884032,cg20051772\n",
+      "cg16570507,cg04433322,cg05884032,cg15059851\n",
+      "cg16570507,cg04433322,cg05884032,cg08375658\n",
+      "cg16570507,cg04433322,cg05884032,cg07925549\n",
+      "cg16570507,cg04433322,cg05884032,cg21298408\n",
+      "cg16570507,cg04433322,cg05884032,cg07552803\n",
+      "cg16570507,cg04433322,cg05884032,cg20248866\n",
+      "cg16570507,cg04433322,cg05884032,cg02329916\n",
+      "cg16570507,cg04433322,cg05884032,cg20596724\n",
+      "cg16570507,cg04433322,cg05884032,cg12610471\n",
+      "cg16570507,cg04433322,cg02547394,cg00213123\n",
+      "cg16570507,cg04433322,cg02547394,cg20051772\n",
+      "cg16570507,cg04433322,cg02547394,cg15059851\n",
+      "cg16570507,cg04433322,cg02547394,cg08375658\n",
+      "cg16570507,cg04433322,cg02547394,cg07925549\n",
+      "cg16570507,cg04433322,cg02547394,cg21298408\n",
+      "cg16570507,cg04433322,cg02547394,cg07552803\n",
+      "cg16570507,cg04433322,cg02547394,cg20248866\n",
+      "cg16570507,cg04433322,cg02547394,cg02329916\n",
+      "cg16570507,cg04433322,cg02547394,cg20596724\n",
+      "cg16570507,cg04433322,cg02547394,cg12610471\n",
+      "cg16570507,cg04433322,cg24073122,cg00213123\n",
+      "cg16570507,cg04433322,cg24073122,cg20051772\n",
+      "cg16570507,cg04433322,cg24073122,cg15059851\n",
+      "cg16570507,cg04433322,cg24073122,cg08375658\n",
+      "cg16570507,cg04433322,cg24073122,cg07925549\n",
+      "cg16570507,cg04433322,cg24073122,cg21298408\n",
+      "cg16570507,cg04433322,cg24073122,cg07552803\n",
+      "cg16570507,cg04433322,cg24073122,cg20248866\n",
+      "cg16570507,cg04433322,cg24073122,cg02329916\n",
+      "cg16570507,cg04433322,cg24073122,cg20596724\n",
+      "cg16570507,cg04433322,cg24073122,cg12610471\n",
+      "cg16570507,cg14153654,cg00727675,cg00213123\n",
+      "cg16570507,cg14153654,cg00727675,cg20051772\n",
+      "cg16570507,cg14153654,cg00727675,cg15059851\n",
+      "cg16570507,cg14153654,cg00727675,cg08375658\n",
+      "cg16570507,cg14153654,cg00727675,cg07925549\n",
+      "cg16570507,cg14153654,cg00727675,cg21298408\n",
+      "cg16570507,cg14153654,cg00727675,cg07552803\n",
+      "cg16570507,cg14153654,cg00727675,cg20248866\n",
+      "cg16570507,cg14153654,cg00727675,cg02329916\n",
+      "cg16570507,cg14153654,cg00727675,cg20596724\n",
+      "cg16570507,cg14153654,cg00727675,cg12610471\n",
+      "cg16570507,cg14153654,cg22500132,cg00213123\n",
+      "cg16570507,cg14153654,cg22500132,cg20051772\n",
+      "cg16570507,cg14153654,cg22500132,cg15059851\n",
+      "cg16570507,cg14153654,cg22500132,cg08375658\n",
+      "cg16570507,cg14153654,cg22500132,cg07925549\n",
+      "cg16570507,cg14153654,cg22500132,cg21298408\n",
+      "cg16570507,cg14153654,cg22500132,cg07552803\n",
+      "cg16570507,cg14153654,cg22500132,cg20248866\n",
+      "cg16570507,cg14153654,cg22500132,cg02329916\n",
+      "cg16570507,cg14153654,cg22500132,cg20596724\n",
+      "cg16570507,cg14153654,cg22500132,cg12610471\n",
+      "cg16570507,cg14153654,cg22746058,cg00213123\n",
+      "cg16570507,cg14153654,cg22746058,cg20051772\n",
+      "cg16570507,cg14153654,cg22746058,cg15059851\n",
+      "cg16570507,cg14153654,cg22746058,cg08375658\n",
+      "cg16570507,cg14153654,cg22746058,cg07925549\n",
+      "cg16570507,cg14153654,cg22746058,cg21298408\n",
+      "cg16570507,cg14153654,cg22746058,cg07552803\n",
+      "cg16570507,cg14153654,cg22746058,cg20248866\n",
+      "cg16570507,cg14153654,cg22746058,cg02329916\n",
+      "cg16570507,cg14153654,cg22746058,cg20596724\n",
+      "cg16570507,cg14153654,cg22746058,cg12610471\n",
+      "cg16570507,cg14153654,cg05884032,cg00213123\n",
+      "cg16570507,cg14153654,cg05884032,cg20051772\n",
+      "cg16570507,cg14153654,cg05884032,cg15059851\n",
+      "cg16570507,cg14153654,cg05884032,cg08375658\n",
+      "cg16570507,cg14153654,cg05884032,cg07925549\n",
+      "cg16570507,cg14153654,cg05884032,cg21298408\n",
+      "cg16570507,cg14153654,cg05884032,cg07552803\n",
+      "cg16570507,cg14153654,cg05884032,cg20248866\n",
+      "cg16570507,cg14153654,cg05884032,cg02329916\n",
+      "cg16570507,cg14153654,cg05884032,cg20596724\n",
+      "cg16570507,cg14153654,cg05884032,cg12610471\n",
+      "cg16570507,cg14153654,cg02547394,cg00213123\n",
+      "cg16570507,cg14153654,cg02547394,cg20051772\n",
+      "cg16570507,cg14153654,cg02547394,cg15059851\n",
+      "cg16570507,cg14153654,cg02547394,cg08375658\n",
+      "cg16570507,cg14153654,cg02547394,cg07925549\n",
+      "cg16570507,cg14153654,cg02547394,cg21298408\n",
+      "cg16570507,cg14153654,cg02547394,cg07552803\n",
+      "cg16570507,cg14153654,cg02547394,cg20248866\n",
+      "cg16570507,cg14153654,cg02547394,cg02329916\n",
+      "cg16570507,cg14153654,cg02547394,cg20596724\n",
+      "cg16570507,cg14153654,cg02547394,cg12610471\n",
+      "cg16570507,cg14153654,cg24073122,cg00213123\n",
+      "cg16570507,cg14153654,cg24073122,cg20051772\n",
+      "cg16570507,cg14153654,cg24073122,cg15059851\n",
+      "cg16570507,cg14153654,cg24073122,cg08375658\n",
+      "cg16570507,cg14153654,cg24073122,cg07925549\n",
+      "cg16570507,cg14153654,cg24073122,cg21298408\n",
+      "cg16570507,cg14153654,cg24073122,cg07552803\n",
+      "cg16570507,cg14153654,cg24073122,cg20248866\n",
+      "cg16570507,cg14153654,cg24073122,cg02329916\n",
+      "cg16570507,cg14153654,cg24073122,cg20596724\n",
+      "cg16570507,cg14153654,cg24073122,cg12610471\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 根據 Cluster 分組\n",
+    "import pandas as pd\n",
+    "import itertools\n",
+    "grouped = df_cluster_select.groupby('cluster')\n",
+    "\n",
+    "# 生成排列組合\n",
+    "combinations = list(itertools.product(*[group.values.tolist() for _, group in grouped]))\n",
+    "# print(combinations)\n",
+    "# 將結果轉換為所需格式\n",
+    "result = []\n",
+    "for combo in combinations:\n",
+    "    result.append([row[2] for row in combo])  # row[0] 對應的是 Gene 列\n",
+    "print(result[0])\n",
+    "print(len(result[0]))\n",
+    "# 打印結果\n",
+    "for combo in result:\n",
+    "\n",
+    "    a = 0\n",
+    "    for i in combo:\n",
+    "        if(a == (len(result[0])-1)):\n",
+    "            print(i,end='\\n')\n",
+    "            a = 0\n",
+    "            continue\n",
+    "        else:\n",
+    "            print(i,end=',')\n",
+    "        a+=1\n",
+    "    "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/process/ics_aba/all_beta_value_GSE243529.ipynb b/process/ics_aba/all_beta_value_GSE243529.ipynb
new file mode 100644
index 0000000..a59cb69
--- /dev/null
+++ b/process/ics_aba/all_beta_value_GSE243529.ipynb
@@ -0,0 +1,4881 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>515</th>\n",
+       "      <th>516</th>\n",
+       "      <th>517</th>\n",
+       "      <th>518</th>\n",
+       "      <th>519</th>\n",
+       "      <th>520</th>\n",
+       "      <th>521</th>\n",
+       "      <th>522</th>\n",
+       "      <th>523</th>\n",
+       "      <th>524</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg07881041</td>\n",
+       "      <td>0.891637</td>\n",
+       "      <td>0.891637</td>\n",
+       "      <td>0.932066</td>\n",
+       "      <td>0.932066</td>\n",
+       "      <td>0.940202</td>\n",
+       "      <td>0.940202</td>\n",
+       "      <td>0.945641</td>\n",
+       "      <td>0.945641</td>\n",
+       "      <td>0.940250</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.927144</td>\n",
+       "      <td>0.927144</td>\n",
+       "      <td>0.954413</td>\n",
+       "      <td>0.954413</td>\n",
+       "      <td>0.960868</td>\n",
+       "      <td>0.960868</td>\n",
+       "      <td>0.943230</td>\n",
+       "      <td>0.943230</td>\n",
+       "      <td>0.946855</td>\n",
+       "      <td>0.946855</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg03513874</td>\n",
+       "      <td>0.942312</td>\n",
+       "      <td>0.942312</td>\n",
+       "      <td>0.935187</td>\n",
+       "      <td>0.935187</td>\n",
+       "      <td>0.964009</td>\n",
+       "      <td>0.964009</td>\n",
+       "      <td>0.966716</td>\n",
+       "      <td>0.966716</td>\n",
+       "      <td>0.945237</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.949742</td>\n",
+       "      <td>0.949742</td>\n",
+       "      <td>0.942481</td>\n",
+       "      <td>0.942481</td>\n",
+       "      <td>0.964317</td>\n",
+       "      <td>0.964317</td>\n",
+       "      <td>0.945584</td>\n",
+       "      <td>0.945584</td>\n",
+       "      <td>0.962746</td>\n",
+       "      <td>0.962746</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg05451842</td>\n",
+       "      <td>0.029975</td>\n",
+       "      <td>0.029975</td>\n",
+       "      <td>0.022880</td>\n",
+       "      <td>0.022880</td>\n",
+       "      <td>0.017531</td>\n",
+       "      <td>0.017531</td>\n",
+       "      <td>0.026281</td>\n",
+       "      <td>0.026281</td>\n",
+       "      <td>0.034589</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.030706</td>\n",
+       "      <td>0.030706</td>\n",
+       "      <td>0.025217</td>\n",
+       "      <td>0.025217</td>\n",
+       "      <td>0.019059</td>\n",
+       "      <td>0.019059</td>\n",
+       "      <td>0.031791</td>\n",
+       "      <td>0.031791</td>\n",
+       "      <td>0.017954</td>\n",
+       "      <td>0.017954</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg14797042</td>\n",
+       "      <td>0.983277</td>\n",
+       "      <td>0.983277</td>\n",
+       "      <td>0.989621</td>\n",
+       "      <td>0.989621</td>\n",
+       "      <td>0.987711</td>\n",
+       "      <td>0.987711</td>\n",
+       "      <td>0.960712</td>\n",
+       "      <td>0.960712</td>\n",
+       "      <td>0.966604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.973674</td>\n",
+       "      <td>0.973674</td>\n",
+       "      <td>0.971978</td>\n",
+       "      <td>0.971978</td>\n",
+       "      <td>0.968671</td>\n",
+       "      <td>0.968671</td>\n",
+       "      <td>0.966904</td>\n",
+       "      <td>0.966904</td>\n",
+       "      <td>0.972501</td>\n",
+       "      <td>0.972501</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg09838562</td>\n",
+       "      <td>0.009447</td>\n",
+       "      <td>0.009447</td>\n",
+       "      <td>0.009020</td>\n",
+       "      <td>0.009020</td>\n",
+       "      <td>0.007164</td>\n",
+       "      <td>0.007164</td>\n",
+       "      <td>0.007786</td>\n",
+       "      <td>0.007786</td>\n",
+       "      <td>0.024895</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.009642</td>\n",
+       "      <td>0.009642</td>\n",
+       "      <td>0.012426</td>\n",
+       "      <td>0.012426</td>\n",
+       "      <td>0.020793</td>\n",
+       "      <td>0.020793</td>\n",
+       "      <td>0.014402</td>\n",
+       "      <td>0.014402</td>\n",
+       "      <td>0.018484</td>\n",
+       "      <td>0.018484</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>736420</th>\n",
+       "      <td>cg19812938</td>\n",
+       "      <td>0.867959</td>\n",
+       "      <td>0.867959</td>\n",
+       "      <td>0.903661</td>\n",
+       "      <td>0.903661</td>\n",
+       "      <td>0.890041</td>\n",
+       "      <td>0.890041</td>\n",
+       "      <td>0.896655</td>\n",
+       "      <td>0.896655</td>\n",
+       "      <td>0.859622</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.878742</td>\n",
+       "      <td>0.878742</td>\n",
+       "      <td>0.899942</td>\n",
+       "      <td>0.899942</td>\n",
+       "      <td>0.897113</td>\n",
+       "      <td>0.897113</td>\n",
+       "      <td>0.885093</td>\n",
+       "      <td>0.885093</td>\n",
+       "      <td>0.878564</td>\n",
+       "      <td>0.878564</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>736421</th>\n",
+       "      <td>cg06272054</td>\n",
+       "      <td>0.008151</td>\n",
+       "      <td>0.008151</td>\n",
+       "      <td>0.011305</td>\n",
+       "      <td>0.011305</td>\n",
+       "      <td>0.011354</td>\n",
+       "      <td>0.011354</td>\n",
+       "      <td>0.009927</td>\n",
+       "      <td>0.009927</td>\n",
+       "      <td>0.008303</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.016021</td>\n",
+       "      <td>0.016021</td>\n",
+       "      <td>0.012377</td>\n",
+       "      <td>0.012377</td>\n",
+       "      <td>0.011960</td>\n",
+       "      <td>0.011960</td>\n",
+       "      <td>0.006381</td>\n",
+       "      <td>0.006381</td>\n",
+       "      <td>0.014298</td>\n",
+       "      <td>0.014298</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>736422</th>\n",
+       "      <td>cg07255356</td>\n",
+       "      <td>0.017649</td>\n",
+       "      <td>0.017649</td>\n",
+       "      <td>0.016949</td>\n",
+       "      <td>0.016949</td>\n",
+       "      <td>0.022004</td>\n",
+       "      <td>0.022004</td>\n",
+       "      <td>0.019642</td>\n",
+       "      <td>0.019642</td>\n",
+       "      <td>0.027163</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.020522</td>\n",
+       "      <td>0.020522</td>\n",
+       "      <td>0.013245</td>\n",
+       "      <td>0.013245</td>\n",
+       "      <td>0.021643</td>\n",
+       "      <td>0.021643</td>\n",
+       "      <td>0.024515</td>\n",
+       "      <td>0.024515</td>\n",
+       "      <td>0.029187</td>\n",
+       "      <td>0.029187</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>736423</th>\n",
+       "      <td>cg24220897</td>\n",
+       "      <td>0.932095</td>\n",
+       "      <td>0.932095</td>\n",
+       "      <td>0.921312</td>\n",
+       "      <td>0.921312</td>\n",
+       "      <td>0.946663</td>\n",
+       "      <td>0.946663</td>\n",
+       "      <td>0.965407</td>\n",
+       "      <td>0.965407</td>\n",
+       "      <td>0.949585</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.923381</td>\n",
+       "      <td>0.923381</td>\n",
+       "      <td>0.861654</td>\n",
+       "      <td>0.861654</td>\n",
+       "      <td>0.904196</td>\n",
+       "      <td>0.904196</td>\n",
+       "      <td>0.929799</td>\n",
+       "      <td>0.929799</td>\n",
+       "      <td>0.953917</td>\n",
+       "      <td>0.953917</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>736424</th>\n",
+       "      <td>cg12325588</td>\n",
+       "      <td>0.013883</td>\n",
+       "      <td>0.013883</td>\n",
+       "      <td>0.006455</td>\n",
+       "      <td>0.006455</td>\n",
+       "      <td>0.006675</td>\n",
+       "      <td>0.006675</td>\n",
+       "      <td>0.005840</td>\n",
+       "      <td>0.005840</td>\n",
+       "      <td>0.019492</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.013614</td>\n",
+       "      <td>0.013614</td>\n",
+       "      <td>0.021223</td>\n",
+       "      <td>0.021223</td>\n",
+       "      <td>0.013646</td>\n",
+       "      <td>0.013646</td>\n",
+       "      <td>0.015869</td>\n",
+       "      <td>0.015869</td>\n",
+       "      <td>0.024592</td>\n",
+       "      <td>0.024592</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>736425 rows × 525 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unnamed: 0         1         2         3         4         5  \\\n",
+       "0       cg07881041  0.891637  0.891637  0.932066  0.932066  0.940202   \n",
+       "1       cg03513874  0.942312  0.942312  0.935187  0.935187  0.964009   \n",
+       "2       cg05451842  0.029975  0.029975  0.022880  0.022880  0.017531   \n",
+       "3       cg14797042  0.983277  0.983277  0.989621  0.989621  0.987711   \n",
+       "4       cg09838562  0.009447  0.009447  0.009020  0.009020  0.007164   \n",
+       "...            ...       ...       ...       ...       ...       ...   \n",
+       "736420  cg19812938  0.867959  0.867959  0.903661  0.903661  0.890041   \n",
+       "736421  cg06272054  0.008151  0.008151  0.011305  0.011305  0.011354   \n",
+       "736422  cg07255356  0.017649  0.017649  0.016949  0.016949  0.022004   \n",
+       "736423  cg24220897  0.932095  0.932095  0.921312  0.921312  0.946663   \n",
+       "736424  cg12325588  0.013883  0.013883  0.006455  0.006455  0.006675   \n",
+       "\n",
+       "               6         7         8         9  ...       515       516  \\\n",
+       "0       0.940202  0.945641  0.945641  0.940250  ...  0.927144  0.927144   \n",
+       "1       0.964009  0.966716  0.966716  0.945237  ...  0.949742  0.949742   \n",
+       "2       0.017531  0.026281  0.026281  0.034589  ...  0.030706  0.030706   \n",
+       "3       0.987711  0.960712  0.960712  0.966604  ...  0.973674  0.973674   \n",
+       "4       0.007164  0.007786  0.007786  0.024895  ...  0.009642  0.009642   \n",
+       "...          ...       ...       ...       ...  ...       ...       ...   \n",
+       "736420  0.890041  0.896655  0.896655  0.859622  ...  0.878742  0.878742   \n",
+       "736421  0.011354  0.009927  0.009927  0.008303  ...  0.016021  0.016021   \n",
+       "736422  0.022004  0.019642  0.019642  0.027163  ...  0.020522  0.020522   \n",
+       "736423  0.946663  0.965407  0.965407  0.949585  ...  0.923381  0.923381   \n",
+       "736424  0.006675  0.005840  0.005840  0.019492  ...  0.013614  0.013614   \n",
+       "\n",
+       "             517       518       519       520       521       522       523  \\\n",
+       "0       0.954413  0.954413  0.960868  0.960868  0.943230  0.943230  0.946855   \n",
+       "1       0.942481  0.942481  0.964317  0.964317  0.945584  0.945584  0.962746   \n",
+       "2       0.025217  0.025217  0.019059  0.019059  0.031791  0.031791  0.017954   \n",
+       "3       0.971978  0.971978  0.968671  0.968671  0.966904  0.966904  0.972501   \n",
+       "4       0.012426  0.012426  0.020793  0.020793  0.014402  0.014402  0.018484   \n",
+       "...          ...       ...       ...       ...       ...       ...       ...   \n",
+       "736420  0.899942  0.899942  0.897113  0.897113  0.885093  0.885093  0.878564   \n",
+       "736421  0.012377  0.012377  0.011960  0.011960  0.006381  0.006381  0.014298   \n",
+       "736422  0.013245  0.013245  0.021643  0.021643  0.024515  0.024515  0.029187   \n",
+       "736423  0.861654  0.861654  0.904196  0.904196  0.929799  0.929799  0.953917   \n",
+       "736424  0.021223  0.021223  0.013646  0.013646  0.015869  0.015869  0.024592   \n",
+       "\n",
+       "             524  \n",
+       "0       0.946855  \n",
+       "1       0.962746  \n",
+       "2       0.017954  \n",
+       "3       0.972501  \n",
+       "4       0.018484  \n",
+       "...          ...  \n",
+       "736420  0.878564  \n",
+       "736421  0.014298  \n",
+       "736422  0.029187  \n",
+       "736423  0.953917  \n",
+       "736424  0.024592  \n",
+       "\n",
+       "[736425 rows x 525 columns]"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "df_beta_0 = pd.read_csv(\"source/GSE243529/all_beta_normalized_0.csv\")\n",
+    "df_beta_0\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "\n",
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
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+       "      <th>515</th>\n",
+       "      <th>516</th>\n",
+       "      <th>517</th>\n",
+       "      <th>518</th>\n",
+       "      <th>519</th>\n",
+       "      <th>520</th>\n",
+       "      <th>521</th>\n",
+       "      <th>522</th>\n",
+       "      <th>523</th>\n",
+       "      <th>524</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg07881041</td>\n",
+       "      <td>0.944083</td>\n",
+       "      <td>0.944083</td>\n",
+       "      <td>0.950317</td>\n",
+       "      <td>0.950317</td>\n",
+       "      <td>0.934376</td>\n",
+       "      <td>0.934376</td>\n",
+       "      <td>0.957498</td>\n",
+       "      <td>0.957498</td>\n",
+       "      <td>0.941509</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.946169</td>\n",
+       "      <td>0.946169</td>\n",
+       "      <td>0.930692</td>\n",
+       "      <td>0.930692</td>\n",
+       "      <td>0.944137</td>\n",
+       "      <td>0.944137</td>\n",
+       "      <td>0.932917</td>\n",
+       "      <td>0.932917</td>\n",
+       "      <td>0.939890</td>\n",
+       "      <td>0.939890</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg03513874</td>\n",
+       "      <td>0.943296</td>\n",
+       "      <td>0.943296</td>\n",
+       "      <td>0.957903</td>\n",
+       "      <td>0.957903</td>\n",
+       "      <td>0.965949</td>\n",
+       "      <td>0.965949</td>\n",
+       "      <td>0.970510</td>\n",
+       "      <td>0.970510</td>\n",
+       "      <td>0.968608</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.951368</td>\n",
+       "      <td>0.951368</td>\n",
+       "      <td>0.950666</td>\n",
+       "      <td>0.950666</td>\n",
+       "      <td>0.942166</td>\n",
+       "      <td>0.942166</td>\n",
+       "      <td>0.939584</td>\n",
+       "      <td>0.939584</td>\n",
+       "      <td>0.945780</td>\n",
+       "      <td>0.945780</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg05451842</td>\n",
+       "      <td>0.012583</td>\n",
+       "      <td>0.012583</td>\n",
+       "      <td>0.031774</td>\n",
+       "      <td>0.031774</td>\n",
+       "      <td>0.034041</td>\n",
+       "      <td>0.034041</td>\n",
+       "      <td>0.028683</td>\n",
+       "      <td>0.028683</td>\n",
+       "      <td>0.018919</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.031586</td>\n",
+       "      <td>0.031586</td>\n",
+       "      <td>0.050621</td>\n",
+       "      <td>0.050621</td>\n",
+       "      <td>0.045672</td>\n",
+       "      <td>0.045672</td>\n",
+       "      <td>0.054436</td>\n",
+       "      <td>0.054436</td>\n",
+       "      <td>0.044102</td>\n",
+       "      <td>0.044102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg14797042</td>\n",
+       "      <td>0.989079</td>\n",
+       "      <td>0.989079</td>\n",
+       "      <td>0.967984</td>\n",
+       "      <td>0.967984</td>\n",
+       "      <td>0.978704</td>\n",
+       "      <td>0.978704</td>\n",
+       "      <td>0.984951</td>\n",
+       "      <td>0.984951</td>\n",
+       "      <td>0.981025</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.980980</td>\n",
+       "      <td>0.980980</td>\n",
+       "      <td>0.975220</td>\n",
+       "      <td>0.975220</td>\n",
+       "      <td>0.985862</td>\n",
+       "      <td>0.985862</td>\n",
+       "      <td>0.965568</td>\n",
+       "      <td>0.965568</td>\n",
+       "      <td>0.965593</td>\n",
+       "      <td>0.965593</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg09838562</td>\n",
+       "      <td>0.009669</td>\n",
+       "      <td>0.009669</td>\n",
+       "      <td>0.019528</td>\n",
+       "      <td>0.019528</td>\n",
+       "      <td>0.015799</td>\n",
+       "      <td>0.015799</td>\n",
+       "      <td>0.014932</td>\n",
+       "      <td>0.014932</td>\n",
+       "      <td>0.009279</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.019250</td>\n",
+       "      <td>0.019250</td>\n",
+       "      <td>0.011791</td>\n",
+       "      <td>0.011791</td>\n",
+       "      <td>0.021468</td>\n",
+       "      <td>0.021468</td>\n",
+       "      <td>0.016349</td>\n",
+       "      <td>0.016349</td>\n",
+       "      <td>0.027341</td>\n",
+       "      <td>0.027341</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>734768</th>\n",
+       "      <td>cg19812938</td>\n",
+       "      <td>0.881670</td>\n",
+       "      <td>0.881670</td>\n",
+       "      <td>0.884738</td>\n",
+       "      <td>0.884738</td>\n",
+       "      <td>0.869154</td>\n",
+       "      <td>0.869154</td>\n",
+       "      <td>0.869164</td>\n",
+       "      <td>0.869164</td>\n",
+       "      <td>0.873994</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.889017</td>\n",
+       "      <td>0.889017</td>\n",
+       "      <td>0.879561</td>\n",
+       "      <td>0.879561</td>\n",
+       "      <td>0.884909</td>\n",
+       "      <td>0.884909</td>\n",
+       "      <td>0.872281</td>\n",
+       "      <td>0.872281</td>\n",
+       "      <td>0.883036</td>\n",
+       "      <td>0.883036</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>734769</th>\n",
+       "      <td>cg06272054</td>\n",
+       "      <td>0.008530</td>\n",
+       "      <td>0.008530</td>\n",
+       "      <td>0.016282</td>\n",
+       "      <td>0.016282</td>\n",
+       "      <td>0.012065</td>\n",
+       "      <td>0.012065</td>\n",
+       "      <td>0.004796</td>\n",
+       "      <td>0.004796</td>\n",
+       "      <td>0.004077</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.010472</td>\n",
+       "      <td>0.010472</td>\n",
+       "      <td>0.015969</td>\n",
+       "      <td>0.015969</td>\n",
+       "      <td>0.018077</td>\n",
+       "      <td>0.018077</td>\n",
+       "      <td>0.015717</td>\n",
+       "      <td>0.015717</td>\n",
+       "      <td>0.014337</td>\n",
+       "      <td>0.014337</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>734770</th>\n",
+       "      <td>cg07255356</td>\n",
+       "      <td>0.013267</td>\n",
+       "      <td>0.013267</td>\n",
+       "      <td>0.022901</td>\n",
+       "      <td>0.022901</td>\n",
+       "      <td>0.019380</td>\n",
+       "      <td>0.019380</td>\n",
+       "      <td>0.021374</td>\n",
+       "      <td>0.021374</td>\n",
+       "      <td>0.012466</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.021260</td>\n",
+       "      <td>0.021260</td>\n",
+       "      <td>0.024679</td>\n",
+       "      <td>0.024679</td>\n",
+       "      <td>0.029346</td>\n",
+       "      <td>0.029346</td>\n",
+       "      <td>0.027983</td>\n",
+       "      <td>0.027983</td>\n",
+       "      <td>0.035189</td>\n",
+       "      <td>0.035189</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>734771</th>\n",
+       "      <td>cg24220897</td>\n",
+       "      <td>0.934471</td>\n",
+       "      <td>0.934471</td>\n",
+       "      <td>0.944143</td>\n",
+       "      <td>0.944143</td>\n",
+       "      <td>0.884108</td>\n",
+       "      <td>0.884108</td>\n",
+       "      <td>0.954730</td>\n",
+       "      <td>0.954730</td>\n",
+       "      <td>0.944178</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.944823</td>\n",
+       "      <td>0.944823</td>\n",
+       "      <td>0.900550</td>\n",
+       "      <td>0.900550</td>\n",
+       "      <td>0.938926</td>\n",
+       "      <td>0.938926</td>\n",
+       "      <td>0.903242</td>\n",
+       "      <td>0.903242</td>\n",
+       "      <td>0.943392</td>\n",
+       "      <td>0.943392</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>734772</th>\n",
+       "      <td>cg12325588</td>\n",
+       "      <td>0.009191</td>\n",
+       "      <td>0.009191</td>\n",
+       "      <td>0.020858</td>\n",
+       "      <td>0.020858</td>\n",
+       "      <td>0.017131</td>\n",
+       "      <td>0.017131</td>\n",
+       "      <td>0.014907</td>\n",
+       "      <td>0.014907</td>\n",
+       "      <td>0.012069</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.019627</td>\n",
+       "      <td>0.019627</td>\n",
+       "      <td>0.016740</td>\n",
+       "      <td>0.016740</td>\n",
+       "      <td>0.025814</td>\n",
+       "      <td>0.025814</td>\n",
+       "      <td>0.032043</td>\n",
+       "      <td>0.032043</td>\n",
+       "      <td>0.019799</td>\n",
+       "      <td>0.019799</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>734773 rows × 523 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unnamed: 0         1         2         3         4         5  \\\n",
+       "0       cg07881041  0.944083  0.944083  0.950317  0.950317  0.934376   \n",
+       "1       cg03513874  0.943296  0.943296  0.957903  0.957903  0.965949   \n",
+       "2       cg05451842  0.012583  0.012583  0.031774  0.031774  0.034041   \n",
+       "3       cg14797042  0.989079  0.989079  0.967984  0.967984  0.978704   \n",
+       "4       cg09838562  0.009669  0.009669  0.019528  0.019528  0.015799   \n",
+       "...            ...       ...       ...       ...       ...       ...   \n",
+       "734768  cg19812938  0.881670  0.881670  0.884738  0.884738  0.869154   \n",
+       "734769  cg06272054  0.008530  0.008530  0.016282  0.016282  0.012065   \n",
+       "734770  cg07255356  0.013267  0.013267  0.022901  0.022901  0.019380   \n",
+       "734771  cg24220897  0.934471  0.934471  0.944143  0.944143  0.884108   \n",
+       "734772  cg12325588  0.009191  0.009191  0.020858  0.020858  0.017131   \n",
+       "\n",
+       "               6         7         8         9  ...       515       516  \\\n",
+       "0       0.934376  0.957498  0.957498  0.941509  ...  0.946169  0.946169   \n",
+       "1       0.965949  0.970510  0.970510  0.968608  ...  0.951368  0.951368   \n",
+       "2       0.034041  0.028683  0.028683  0.018919  ...  0.031586  0.031586   \n",
+       "3       0.978704  0.984951  0.984951  0.981025  ...  0.980980  0.980980   \n",
+       "4       0.015799  0.014932  0.014932  0.009279  ...  0.019250  0.019250   \n",
+       "...          ...       ...       ...       ...  ...       ...       ...   \n",
+       "734768  0.869154  0.869164  0.869164  0.873994  ...  0.889017  0.889017   \n",
+       "734769  0.012065  0.004796  0.004796  0.004077  ...  0.010472  0.010472   \n",
+       "734770  0.019380  0.021374  0.021374  0.012466  ...  0.021260  0.021260   \n",
+       "734771  0.884108  0.954730  0.954730  0.944178  ...  0.944823  0.944823   \n",
+       "734772  0.017131  0.014907  0.014907  0.012069  ...  0.019627  0.019627   \n",
+       "\n",
+       "             517       518       519       520       521       522       523  \\\n",
+       "0       0.930692  0.930692  0.944137  0.944137  0.932917  0.932917  0.939890   \n",
+       "1       0.950666  0.950666  0.942166  0.942166  0.939584  0.939584  0.945780   \n",
+       "2       0.050621  0.050621  0.045672  0.045672  0.054436  0.054436  0.044102   \n",
+       "3       0.975220  0.975220  0.985862  0.985862  0.965568  0.965568  0.965593   \n",
+       "4       0.011791  0.011791  0.021468  0.021468  0.016349  0.016349  0.027341   \n",
+       "...          ...       ...       ...       ...       ...       ...       ...   \n",
+       "734768  0.879561  0.879561  0.884909  0.884909  0.872281  0.872281  0.883036   \n",
+       "734769  0.015969  0.015969  0.018077  0.018077  0.015717  0.015717  0.014337   \n",
+       "734770  0.024679  0.024679  0.029346  0.029346  0.027983  0.027983  0.035189   \n",
+       "734771  0.900550  0.900550  0.938926  0.938926  0.903242  0.903242  0.943392   \n",
+       "734772  0.016740  0.016740  0.025814  0.025814  0.032043  0.032043  0.019799   \n",
+       "\n",
+       "             524  \n",
+       "0       0.939890  \n",
+       "1       0.945780  \n",
+       "2       0.044102  \n",
+       "3       0.965593  \n",
+       "4       0.027341  \n",
+       "...          ...  \n",
+       "734768  0.883036  \n",
+       "734769  0.014337  \n",
+       "734770  0.035189  \n",
+       "734771  0.943392  \n",
+       "734772  0.019799  \n",
+       "\n",
+       "[734773 rows x 523 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_beta_1 = pd.read_csv(\"source/GSE243529/all_beta_normalized_1.csv\")\n",
+    "df_beta_1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "        Unnamed: 0       1_x       2_x       3_x       4_x       5_x  \\\n",
+      "0       cg07881041  0.891637  0.891637  0.932066  0.932066  0.940202   \n",
+      "1       cg03513874  0.942312  0.942312  0.935187  0.935187  0.964009   \n",
+      "2       cg05451842  0.029975  0.029975  0.022880  0.022880  0.017531   \n",
+      "3       cg14797042  0.983277  0.983277  0.989621  0.989621  0.987711   \n",
+      "4       cg09838562  0.009447  0.009447  0.009020  0.009020  0.007164   \n",
+      "...            ...       ...       ...       ...       ...       ...   \n",
+      "730294  cg19812938  0.867959  0.867959  0.903661  0.903661  0.890041   \n",
+      "730295  cg06272054  0.008151  0.008151  0.011305  0.011305  0.011354   \n",
+      "730296  cg07255356  0.017649  0.017649  0.016949  0.016949  0.022004   \n",
+      "730297  cg24220897  0.932095  0.932095  0.921312  0.921312  0.946663   \n",
+      "730298  cg12325588  0.013883  0.013883  0.006455  0.006455  0.006675   \n",
+      "\n",
+      "             6_x       7_x       8_x       9_x  ...     515_y     516_y  \\\n",
+      "0       0.940202  0.945641  0.945641  0.940250  ...  0.946169  0.946169   \n",
+      "1       0.964009  0.966716  0.966716  0.945237  ...  0.951368  0.951368   \n",
+      "2       0.017531  0.026281  0.026281  0.034589  ...  0.031586  0.031586   \n",
+      "3       0.987711  0.960712  0.960712  0.966604  ...  0.980980  0.980980   \n",
+      "4       0.007164  0.007786  0.007786  0.024895  ...  0.019250  0.019250   \n",
+      "...          ...       ...       ...       ...  ...       ...       ...   \n",
+      "730294  0.890041  0.896655  0.896655  0.859622  ...  0.889017  0.889017   \n",
+      "730295  0.011354  0.009927  0.009927  0.008303  ...  0.010472  0.010472   \n",
+      "730296  0.022004  0.019642  0.019642  0.027163  ...  0.021260  0.021260   \n",
+      "730297  0.946663  0.965407  0.965407  0.949585  ...  0.944823  0.944823   \n",
+      "730298  0.006675  0.005840  0.005840  0.019492  ...  0.019627  0.019627   \n",
+      "\n",
+      "           517_y     518_y     519_y     520_y     521_y     522_y     523_y  \\\n",
+      "0       0.930692  0.930692  0.944137  0.944137  0.932917  0.932917  0.939890   \n",
+      "1       0.950666  0.950666  0.942166  0.942166  0.939584  0.939584  0.945780   \n",
+      "2       0.050621  0.050621  0.045672  0.045672  0.054436  0.054436  0.044102   \n",
+      "3       0.975220  0.975220  0.985862  0.985862  0.965568  0.965568  0.965593   \n",
+      "4       0.011791  0.011791  0.021468  0.021468  0.016349  0.016349  0.027341   \n",
+      "...          ...       ...       ...       ...       ...       ...       ...   \n",
+      "730294  0.879561  0.879561  0.884909  0.884909  0.872281  0.872281  0.883036   \n",
+      "730295  0.015969  0.015969  0.018077  0.018077  0.015717  0.015717  0.014337   \n",
+      "730296  0.024679  0.024679  0.029346  0.029346  0.027983  0.027983  0.035189   \n",
+      "730297  0.900550  0.900550  0.938926  0.938926  0.903242  0.903242  0.943392   \n",
+      "730298  0.016740  0.016740  0.025814  0.025814  0.032043  0.032043  0.019799   \n",
+      "\n",
+      "           524_y  \n",
+      "0       0.939890  \n",
+      "1       0.945780  \n",
+      "2       0.044102  \n",
+      "3       0.965593  \n",
+      "4       0.027341  \n",
+      "...          ...  \n",
+      "730294  0.883036  \n",
+      "730295  0.014337  \n",
+      "730296  0.035189  \n",
+      "730297  0.943392  \n",
+      "730298  0.019799  \n",
+      "\n",
+      "[730299 rows x 1047 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_beta = pd.merge(df_beta_0,df_beta_1,on=\"Unnamed: 0\")\n",
+    "print(df_beta)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "         0         1         2         3         4         5         6       \\\n",
+      "257_x  0.944491  0.941055  0.019063  0.970588  0.016889  0.968430  0.601347   \n",
+      "259_x  0.936676  0.958219  0.031681  0.985476  0.010134  0.955828  0.604655   \n",
+      "261_x  0.932445  0.954776  0.023602  0.985671  0.005280  0.960710  0.631029   \n",
+      "263_x  0.950438  0.971993  0.025135  0.986416  0.014675  0.980988  0.677755   \n",
+      "265_x  0.935534  0.934625  0.034794  0.965526  0.019106  0.957349  0.592838   \n",
+      "...         ...       ...       ...       ...       ...       ...       ...   \n",
+      "515_x  0.927144  0.949742  0.030706  0.973674  0.009642  0.966152  0.610119   \n",
+      "517_x  0.954413  0.942481  0.025217  0.971978  0.012426  0.964821  0.639148   \n",
+      "519_x  0.960868  0.964317  0.019059  0.968671  0.020793  0.968693  0.637075   \n",
+      "521_x  0.943230  0.945584  0.031791  0.966904  0.014402  0.945293  0.620796   \n",
+      "523_x  0.946855  0.962746  0.017954  0.972501  0.018484  0.974604  0.634016   \n",
+      "\n",
+      "         7         8         9       ...    730289    730290    730291  \\\n",
+      "257_x  0.881432  0.492665  0.455735  ...  0.006310  0.897607  0.946030   \n",
+      "259_x  0.883578  0.587311  0.543591  ...  0.006204  0.930669  0.941054   \n",
+      "261_x  0.875564  0.651469  0.604075  ...  0.007425  0.911097  0.923278   \n",
+      "263_x  0.890447  0.644840  0.666678  ...  0.009980  0.920904  0.951211   \n",
+      "265_x  0.895628  0.568797  0.594449  ...  0.014064  0.898200  0.922606   \n",
+      "...         ...       ...       ...  ...       ...       ...       ...   \n",
+      "515_x  0.890040  0.622046  0.625218  ...  0.017826  0.906962  0.918184   \n",
+      "517_x  0.878195  0.542053  0.639054  ...  0.025804  0.927273  0.919722   \n",
+      "519_x  0.907694  0.675767  0.677234  ...  0.031725  0.902970  0.932410   \n",
+      "521_x  0.881455  0.554374  0.560200  ...  0.012560  0.878921  0.923077   \n",
+      "523_x  0.894717  0.559626  0.535682  ...  0.011249  0.894842  0.924142   \n",
+      "\n",
+      "         730292    730293    730294    730295    730296    730297    730298  \n",
+      "257_x  0.953652  0.832425  0.886375  0.009983  0.021550  0.955338  0.009822  \n",
+      "259_x  0.949772  0.838903  0.892014  0.007293  0.033496  0.935890  0.010103  \n",
+      "261_x  0.940460  0.812506  0.883188  0.012874  0.017124  0.953820  0.006297  \n",
+      "263_x  0.953876  0.892442  0.928424  0.012274  0.012906  0.918379  0.030021  \n",
+      "265_x  0.950515  0.873269  0.895948  0.012924  0.020729  0.905063  0.023880  \n",
+      "...         ...       ...       ...       ...       ...       ...       ...  \n",
+      "515_x  0.949464  0.852938  0.878742  0.016021  0.020522  0.923381  0.013614  \n",
+      "517_x  0.946991  0.797862  0.899942  0.012377  0.013245  0.861654  0.021223  \n",
+      "519_x  0.943649  0.823714  0.897113  0.011960  0.021643  0.904196  0.013646  \n",
+      "521_x  0.938862  0.828313  0.885093  0.006381  0.024515  0.929799  0.015869  \n",
+      "523_x  0.956803  0.834866  0.878564  0.014298  0.029187  0.953917  0.024592  \n",
+      "\n",
+      "[134 rows x 730299 columns]\n",
+      "         0         1         2         3         4         5         6       \\\n",
+      "1_x    0.891637  0.942312  0.029975  0.983277  0.009447  0.963909  0.547637   \n",
+      "3_x    0.932066  0.935187  0.022880  0.989621  0.009020  0.968153  0.630792   \n",
+      "5_x    0.940202  0.964009  0.017531  0.987711  0.007164  0.977007  0.657722   \n",
+      "7_x    0.945641  0.966716  0.026281  0.960712  0.007786  0.963226  0.627110   \n",
+      "9_x    0.940250  0.945237  0.034589  0.966604  0.024895  0.962018  0.648072   \n",
+      "...         ...       ...       ...       ...       ...       ...       ...   \n",
+      "247_x  0.963177  0.950974  0.047110  0.978634  0.012414  0.948015  0.692950   \n",
+      "249_x  0.925103  0.952803  0.022537  0.977123  0.011372  0.960816  0.612208   \n",
+      "251_x  0.935529  0.960803  0.037645  0.973661  0.029905  0.961988  0.644703   \n",
+      "253_x  0.932493  0.947340  0.036287  0.975147  0.016267  0.959567  0.631247   \n",
+      "255_x  0.937540  0.959682  0.034809  0.973619  0.027357  0.958788  0.647232   \n",
+      "\n",
+      "         7         8         9       ...    730289    730290    730291  \\\n",
+      "1_x    0.950321  0.753387  0.669000  ...  0.039640  0.897572  0.927209   \n",
+      "3_x    0.854900  0.529452  0.575943  ...  0.013298  0.914774  0.939838   \n",
+      "5_x    0.909154  0.561784  0.582170  ...  0.014250  0.911914  0.943766   \n",
+      "7_x    0.853463  0.533461  0.619980  ...  0.010525  0.926379  0.938161   \n",
+      "9_x    0.890485  0.544131  0.538939  ...  0.011702  0.885074  0.917745   \n",
+      "...         ...       ...       ...  ...       ...       ...       ...   \n",
+      "247_x  0.876160  0.590291  0.564501  ...  0.009770  0.894481  0.915441   \n",
+      "249_x  0.911642  0.570399  0.592302  ...  0.014391  0.882021  0.930739   \n",
+      "251_x  0.850623  0.534737  0.572251  ...  0.017095  0.894229  0.933776   \n",
+      "253_x  0.837581  0.562682  0.553462  ...  0.016572  0.892738  0.909585   \n",
+      "255_x  0.847405  0.575935  0.710056  ...  0.017406  0.894410  0.916764   \n",
+      "\n",
+      "         730292    730293    730294    730295    730296    730297    730298  \n",
+      "1_x    0.948472  0.792336  0.867959  0.008151  0.017649  0.932095  0.013883  \n",
+      "3_x    0.961787  0.914687  0.903661  0.011305  0.016949  0.921312  0.006455  \n",
+      "5_x    0.947047  0.874900  0.890041  0.011354  0.022004  0.946663  0.006675  \n",
+      "7_x    0.964461  0.905188  0.896655  0.009927  0.019642  0.965407  0.005840  \n",
+      "9_x    0.952082  0.867322  0.859622  0.008303  0.027163  0.949585  0.019492  \n",
+      "...         ...       ...       ...       ...       ...       ...       ...  \n",
+      "247_x  0.935785  0.892077  0.884135  0.007360  0.023650  0.919170  0.005686  \n",
+      "249_x  0.955235  0.823152  0.836735  0.010961  0.016117  0.927281  0.008247  \n",
+      "251_x  0.934698  0.879448  0.874811  0.020254  0.023272  0.901690  0.019272  \n",
+      "253_x  0.949632  0.849505  0.879413  0.008597  0.025104  0.934250  0.021318  \n",
+      "255_x  0.935998  0.872646  0.866350  0.017377  0.032841  0.903291  0.023316  \n",
+      "\n",
+      "[128 rows x 730299 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "import pandas as pd\n",
+    "\n",
+    "tumor_count = 256\n",
+    "_0 = 524 \n",
+    "train_normal_0 = df_beta.iloc[:,tumor_count+1:_0:2].T\n",
+    "train_tumor_0 = df_beta.iloc[:, 1:tumor_count+1:2].T\n",
+    "\n",
+    "print(train_normal_0)\n",
+    "print(train_tumor_0)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "134\n",
+      "         0         1         2         3         4         5         6       \\\n",
+      "1_y    0.944083  0.943296  0.012583  0.989079  0.009669  0.966741  0.622188   \n",
+      "3_y    0.950317  0.957903  0.031774  0.967984  0.019528  0.958993  0.680737   \n",
+      "5_y    0.934376  0.965949  0.034041  0.978704  0.015799  0.968882  0.621227   \n",
+      "7_y    0.957498  0.970510  0.028683  0.984951  0.014932  0.964969  0.656947   \n",
+      "9_y    0.941509  0.968608  0.018919  0.981025  0.009279  0.964774  0.587489   \n",
+      "...         ...       ...       ...       ...       ...       ...       ...   \n",
+      "247_y  0.933164  0.953317  0.029272  0.983260  0.018065  0.968165  0.696745   \n",
+      "249_y  0.940272  0.962836  0.041876  0.965957  0.016495  0.967315  0.612897   \n",
+      "251_y  0.953192  0.944884  0.034416  0.970273  0.018402  0.953568  0.674615   \n",
+      "253_y  0.942201  0.932417  0.052085  0.970230  0.014003  0.958073  0.662412   \n",
+      "255_y  0.939644  0.958758  0.029013  0.963957  0.026137  0.958626  0.654526   \n",
+      "\n",
+      "         7         8         9       ...    730289    730290    730291  \\\n",
+      "1_y    0.879809  0.566474  0.580040  ...  0.006486  0.915614  0.933590   \n",
+      "3_y    0.867633  0.547496  0.632484  ...  0.013535  0.924227  0.923572   \n",
+      "5_y    0.855763  0.538873  0.570404  ...  0.015836  0.931631  0.920583   \n",
+      "7_y    0.868741  0.544339  0.581719  ...  0.013378  0.910470  0.922881   \n",
+      "9_y    0.913547  0.575926  0.660618  ...  0.048633  0.885095  0.919603   \n",
+      "...         ...       ...       ...  ...       ...       ...       ...   \n",
+      "247_y  0.902057  0.634576  0.646066  ...  0.033331  0.910356  0.919106   \n",
+      "249_y  0.777522  0.511915  0.696985  ...  0.019725  0.865318  0.916751   \n",
+      "251_y  0.898157  0.495985  0.543045  ...  0.018069  0.891146  0.930765   \n",
+      "253_y  0.937203  0.508768  0.559363  ...  0.020081  0.871081  0.917148   \n",
+      "255_y  0.874118  0.594128  0.581761  ...  0.013689  0.902405  0.910143   \n",
+      "\n",
+      "         730292    730293    730294    730295    730296    730297    730298  \n",
+      "1_y    0.961454  0.889010  0.881670  0.008530  0.013267  0.934471  0.009191  \n",
+      "3_y    0.953404  0.871591  0.884738  0.016282  0.022901  0.944143  0.020858  \n",
+      "5_y    0.941646  0.867310  0.869154  0.012065  0.019380  0.884108  0.017131  \n",
+      "7_y    0.956457  0.887971  0.869164  0.004796  0.021374  0.954730  0.014907  \n",
+      "9_y    0.966316  0.808480  0.873994  0.004077  0.012466  0.944178  0.012069  \n",
+      "...         ...       ...       ...       ...       ...       ...       ...  \n",
+      "247_y  0.960668  0.902536  0.885621  0.017823  0.017965  0.910968  0.021480  \n",
+      "249_y  0.959807  0.843072  0.900634  0.008236  0.015977  0.936653  0.016717  \n",
+      "251_y  0.938507  0.885130  0.880515  0.011715  0.028832  0.936853  0.015853  \n",
+      "253_y  0.926329  0.866411  0.888477  0.013857  0.035328  0.941731  0.017161  \n",
+      "255_y  0.937106  0.900410  0.901021  0.019691  0.033695  0.932843  0.014222  \n",
+      "\n",
+      "[127 rows x 730299 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "tumor_count = 254\n",
+    "_0_pos = _0+1\n",
+    "_1 = 522\n",
+    "train_normal_1 = df_beta.iloc[:,_0_pos+tumor_count:_0_pos+_1 :2].T\n",
+    "train_tumor_1 = df_beta.iloc[:, _0_pos:_0_pos+tumor_count:2].T\n",
+    "\n",
+    "print(len(train_normal_1))\n",
+    "print(train_tumor_1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "         0         1         2         3         4         5         6       \\\n",
+      "257_x  0.944491  0.941055  0.019063  0.970588  0.016889  0.968430  0.601347   \n",
+      "259_x  0.936676  0.958219  0.031681  0.985476  0.010134  0.955828  0.604655   \n",
+      "261_x  0.932445  0.954776  0.023602  0.985671  0.005280  0.960710  0.631029   \n",
+      "263_x  0.950438  0.971993  0.025135  0.986416  0.014675  0.980988  0.677755   \n",
+      "265_x  0.935534  0.934625  0.034794  0.965526  0.019106  0.957349  0.592838   \n",
+      "...         ...       ...       ...       ...       ...       ...       ...   \n",
+      "247_x  0.963177  0.950974  0.047110  0.978634  0.012414  0.948015  0.692950   \n",
+      "249_x  0.925103  0.952803  0.022537  0.977123  0.011372  0.960816  0.612208   \n",
+      "251_x  0.935529  0.960803  0.037645  0.973661  0.029905  0.961988  0.644703   \n",
+      "253_x  0.932493  0.947340  0.036287  0.975147  0.016267  0.959567  0.631247   \n",
+      "255_x  0.937540  0.959682  0.034809  0.973619  0.027357  0.958788  0.647232   \n",
+      "\n",
+      "         7         8         9       ...    730289    730290    730291  \\\n",
+      "257_x  0.881432  0.492665  0.455735  ...  0.006310  0.897607  0.946030   \n",
+      "259_x  0.883578  0.587311  0.543591  ...  0.006204  0.930669  0.941054   \n",
+      "261_x  0.875564  0.651469  0.604075  ...  0.007425  0.911097  0.923278   \n",
+      "263_x  0.890447  0.644840  0.666678  ...  0.009980  0.920904  0.951211   \n",
+      "265_x  0.895628  0.568797  0.594449  ...  0.014064  0.898200  0.922606   \n",
+      "...         ...       ...       ...  ...       ...       ...       ...   \n",
+      "247_x  0.876160  0.590291  0.564501  ...  0.009770  0.894481  0.915441   \n",
+      "249_x  0.911642  0.570399  0.592302  ...  0.014391  0.882021  0.930739   \n",
+      "251_x  0.850623  0.534737  0.572251  ...  0.017095  0.894229  0.933776   \n",
+      "253_x  0.837581  0.562682  0.553462  ...  0.016572  0.892738  0.909585   \n",
+      "255_x  0.847405  0.575935  0.710056  ...  0.017406  0.894410  0.916764   \n",
+      "\n",
+      "         730292    730293    730294    730295    730296    730297    730298  \n",
+      "257_x  0.953652  0.832425  0.886375  0.009983  0.021550  0.955338  0.009822  \n",
+      "259_x  0.949772  0.838903  0.892014  0.007293  0.033496  0.935890  0.010103  \n",
+      "261_x  0.940460  0.812506  0.883188  0.012874  0.017124  0.953820  0.006297  \n",
+      "263_x  0.953876  0.892442  0.928424  0.012274  0.012906  0.918379  0.030021  \n",
+      "265_x  0.950515  0.873269  0.895948  0.012924  0.020729  0.905063  0.023880  \n",
+      "...         ...       ...       ...       ...       ...       ...       ...  \n",
+      "247_x  0.935785  0.892077  0.884135  0.007360  0.023650  0.919170  0.005686  \n",
+      "249_x  0.955235  0.823152  0.836735  0.010961  0.016117  0.927281  0.008247  \n",
+      "251_x  0.934698  0.879448  0.874811  0.020254  0.023272  0.901690  0.019272  \n",
+      "253_x  0.949632  0.849505  0.879413  0.008597  0.025104  0.934250  0.021318  \n",
+      "255_x  0.935998  0.872646  0.866350  0.017377  0.032841  0.903291  0.023316  \n",
+      "\n",
+      "[262 rows x 730299 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# X1 = train_normal_0.T + train_normal_1.T\n",
+    "X1 = pd.concat([train_normal_0, train_tumor_0], axis=0)\n",
+    "\n",
+    "\n",
+    "if len(train_normal_0):\n",
+    "    y1 = [(0 if i < len(train_normal_0) else 1) for i in range(len(X1))]\n",
+    "# train : 128t/134n = 262  ⇒ 256/268 = 524\n",
+    "# test : 127t/134n = 262 ⇒ 254/268 = 522\n",
+    "\n",
+    "print((X1))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "         0         1         2         3         4         5         6       \\\n",
+      "257_y  0.941835  0.952351  0.033843  0.965625  0.018656  0.971850  0.646164   \n",
+      "259_y  0.950556  0.965640  0.027113  0.974349  0.009933  0.973287  0.664429   \n",
+      "261_y  0.949528  0.957152  0.035225  0.978224  0.006902  0.967282  0.606291   \n",
+      "263_y  0.481182  0.940676  0.036639  0.969736  0.005657  0.927707  0.674127   \n",
+      "265_y  0.947247  0.931571  0.028956  0.980057  0.014180  0.972478  0.662947   \n",
+      "...         ...       ...       ...       ...       ...       ...       ...   \n",
+      "247_y  0.933164  0.953317  0.029272  0.983260  0.018065  0.968165  0.696745   \n",
+      "249_y  0.940272  0.962836  0.041876  0.965957  0.016495  0.967315  0.612897   \n",
+      "251_y  0.953192  0.944884  0.034416  0.970273  0.018402  0.953568  0.674615   \n",
+      "253_y  0.942201  0.932417  0.052085  0.970230  0.014003  0.958073  0.662412   \n",
+      "255_y  0.939644  0.958758  0.029013  0.963957  0.026137  0.958626  0.654526   \n",
+      "\n",
+      "         7         8         9       ...    730289    730290    730291  \\\n",
+      "257_y  0.851468  0.585871  0.644606  ...  0.016719  0.908681  0.932501   \n",
+      "259_y  0.916417  0.679561  0.731845  ...  0.010756  0.927696  0.934060   \n",
+      "261_y  0.857414  0.526725  0.496275  ...  0.020514  0.863676  0.913598   \n",
+      "263_y  0.885300  0.586345  0.621877  ...  0.013610  0.915543  0.923342   \n",
+      "265_y  0.872972  0.656456  0.675041  ...  0.010804  0.875236  0.921637   \n",
+      "...         ...       ...       ...  ...       ...       ...       ...   \n",
+      "247_y  0.902057  0.634576  0.646066  ...  0.033331  0.910356  0.919106   \n",
+      "249_y  0.777522  0.511915  0.696985  ...  0.019725  0.865318  0.916751   \n",
+      "251_y  0.898157  0.495985  0.543045  ...  0.018069  0.891146  0.930765   \n",
+      "253_y  0.937203  0.508768  0.559363  ...  0.020081  0.871081  0.917148   \n",
+      "255_y  0.874118  0.594128  0.581761  ...  0.013689  0.902405  0.910143   \n",
+      "\n",
+      "         730292    730293    730294    730295    730296    730297    730298  \n",
+      "257_y  0.957587  0.914597  0.886147  0.016699  0.020705  0.949263  0.024108  \n",
+      "259_y  0.960047  0.896899  0.890823  0.014341  0.012359  0.935507  0.011456  \n",
+      "261_y  0.941485  0.861490  0.875755  0.012761  0.025194  0.913934  0.011417  \n",
+      "263_y  0.946670  0.830302  0.884796  0.014711  0.025084  0.917105  0.016553  \n",
+      "265_y  0.935619  0.827401  0.886924  0.005517  0.016238  0.923354  0.019376  \n",
+      "...         ...       ...       ...       ...       ...       ...       ...  \n",
+      "247_y  0.960668  0.902536  0.885621  0.017823  0.017965  0.910968  0.021480  \n",
+      "249_y  0.959807  0.843072  0.900634  0.008236  0.015977  0.936653  0.016717  \n",
+      "251_y  0.938507  0.885130  0.880515  0.011715  0.028832  0.936853  0.015853  \n",
+      "253_y  0.926329  0.866411  0.888477  0.013857  0.035328  0.941731  0.017161  \n",
+      "255_y  0.937106  0.900410  0.901021  0.019691  0.033695  0.932843  0.014222  \n",
+      "\n",
+      "[261 rows x 730299 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# X2 = train_normal_1 + train_tumor_1\n",
+    "X2 = pd.concat([train_normal_1, train_tumor_1], axis=0)\n",
+    "\n",
+    "if len(train_normal_1):\n",
+    "    y2 = [(0 if i < len(train_normal_1) else 1) for i in range(len(X2))]\n",
+    "\n",
+    "# train : 128t/134n = 262  ⇒ 256/268 = 524\n",
+    "# test : 127t/134n = 263 ⇒ 254/268 = 522\n",
+    "\n",
+    "print(X2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "訓練集樣本數量： 418\n",
+      "測試集樣本數量： 105\n",
+      "訓練集中各類別樣本數量：\n",
+      "Counter({0: 210, 1: 208})\n",
+      "測試集中各類別樣本數量：\n",
+      "Counter({0: 58, 1: 47})\n"
+     ]
+    }
+   ],
+   "source": [
+    "X =  pd.concat([X1, X2], axis=0)\n",
+    "y = y1 + y2\n",
+    "# print(X)\n",
+    "\n",
+    "test_ratio = 0.2\n",
+    "\n",
+    "seed = 42\n",
+    "\n",
+    "from collections import Counter\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(\n",
+    "    X, y, test_size=test_ratio, random_state=seed\n",
+    ")\n",
+    "\n",
+    "print(f\"訓練集樣本數量： {len(X_train)}\")\n",
+    "print(f\"測試集樣本數量： {len(X_test)}\")\n",
+    "train_class_distribution = Counter(y_train)\n",
+    "val_class_distribution = Counter(y_test)\n",
+    "print(\"訓練集中各類別樣本數量：\")\n",
+    "print(train_class_distribution)\n",
+    "print(\"測試集中各類別樣本數量：\")\n",
+    "print(val_class_distribution)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train[\"label\"] = y_train\n",
+    "X_test[\"label\"] = y_test\n",
+    "\n",
+    "X_train_sorted = X_train.sort_values(by=\"label\")\n",
+    "X_test_sorted = X_test.sort_values(by=\"label\")\n",
+    "\n",
+    "# print(X_train_sorted[X_train_sorted[\"label\"] == 0])\n",
+    "# print(X_train_sorted[X_train_sorted[\"label\"] == 1])\n",
+    "\n",
+    "\n",
+    "\n",
+    "train_normal = X_train_sorted[X_train_sorted[\"label\"] == 0].drop(columns=[\"label\"])\n",
+    "train_tumor = X_train_sorted[X_train_sorted[\"label\"] == 1].drop(columns=[\"label\"])\n",
+    "\n",
+    "\n",
+    "k = train_tumor\n",
+    "kk = train_normal"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "</style>\n",
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>461_x</th>\n",
+       "      <th>487_y</th>\n",
+       "      <th>325_x</th>\n",
+       "      <th>333_x</th>\n",
+       "      <th>417_x</th>\n",
+       "      <th>355_x</th>\n",
+       "      <th>373_y</th>\n",
+       "      <th>329_y</th>\n",
+       "      <th>503_x</th>\n",
+       "      <th>...</th>\n",
+       "      <th>61_x</th>\n",
+       "      <th>171_x</th>\n",
+       "      <th>179_x</th>\n",
+       "      <th>131_y</th>\n",
+       "      <th>51_y</th>\n",
+       "      <th>39_y</th>\n",
+       "      <th>151_y</th>\n",
+       "      <th>225_x</th>\n",
+       "      <th>85_y</th>\n",
+       "      <th>199_x</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg07881041</td>\n",
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+       "      <td>0.931867</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>0.939040</td>\n",
+       "      <td>0.947915</td>\n",
+       "      <td>0.925148</td>\n",
+       "      <td>0.908973</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg03513874</td>\n",
+       "      <td>0.962719</td>\n",
+       "      <td>0.952201</td>\n",
+       "      <td>0.934461</td>\n",
+       "      <td>0.935450</td>\n",
+       "      <td>0.953576</td>\n",
+       "      <td>0.942798</td>\n",
+       "      <td>0.933852</td>\n",
+       "      <td>0.945366</td>\n",
+       "      <td>0.940140</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.953731</td>\n",
+       "      <td>0.954276</td>\n",
+       "      <td>0.944159</td>\n",
+       "      <td>0.964771</td>\n",
+       "      <td>0.951581</td>\n",
+       "      <td>0.956153</td>\n",
+       "      <td>0.959771</td>\n",
+       "      <td>0.968014</td>\n",
+       "      <td>0.938931</td>\n",
+       "      <td>0.946057</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg05451842</td>\n",
+       "      <td>0.025680</td>\n",
+       "      <td>0.029857</td>\n",
+       "      <td>0.021494</td>\n",
+       "      <td>0.042652</td>\n",
+       "      <td>0.036531</td>\n",
+       "      <td>0.026896</td>\n",
+       "      <td>0.027610</td>\n",
+       "      <td>0.043561</td>\n",
+       "      <td>0.051736</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.042091</td>\n",
+       "      <td>0.039476</td>\n",
+       "      <td>0.034699</td>\n",
+       "      <td>0.025350</td>\n",
+       "      <td>0.024445</td>\n",
+       "      <td>0.027273</td>\n",
+       "      <td>0.025966</td>\n",
+       "      <td>0.024816</td>\n",
+       "      <td>0.050523</td>\n",
+       "      <td>0.031266</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg14797042</td>\n",
+       "      <td>0.962476</td>\n",
+       "      <td>0.981526</td>\n",
+       "      <td>0.970098</td>\n",
+       "      <td>0.978789</td>\n",
+       "      <td>0.974692</td>\n",
+       "      <td>0.972280</td>\n",
+       "      <td>0.984615</td>\n",
+       "      <td>0.962927</td>\n",
+       "      <td>0.980575</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.976688</td>\n",
+       "      <td>0.972889</td>\n",
+       "      <td>0.975634</td>\n",
+       "      <td>0.979691</td>\n",
+       "      <td>0.987620</td>\n",
+       "      <td>0.973312</td>\n",
+       "      <td>0.973261</td>\n",
+       "      <td>0.976011</td>\n",
+       "      <td>0.973731</td>\n",
+       "      <td>0.961352</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg09838562</td>\n",
+       "      <td>0.017029</td>\n",
+       "      <td>0.017377</td>\n",
+       "      <td>0.022906</td>\n",
+       "      <td>0.021399</td>\n",
+       "      <td>0.029693</td>\n",
+       "      <td>0.014263</td>\n",
+       "      <td>0.020167</td>\n",
+       "      <td>0.013235</td>\n",
+       "      <td>0.014649</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.012646</td>\n",
+       "      <td>0.016793</td>\n",
+       "      <td>0.025278</td>\n",
+       "      <td>0.015261</td>\n",
+       "      <td>0.003984</td>\n",
+       "      <td>0.008068</td>\n",
+       "      <td>0.011514</td>\n",
+       "      <td>0.012520</td>\n",
+       "      <td>0.021304</td>\n",
+       "      <td>0.027372</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730294</th>\n",
+       "      <td>cg19812938</td>\n",
+       "      <td>0.872371</td>\n",
+       "      <td>0.887197</td>\n",
+       "      <td>0.894871</td>\n",
+       "      <td>0.902936</td>\n",
+       "      <td>0.875369</td>\n",
+       "      <td>0.895061</td>\n",
+       "      <td>0.891872</td>\n",
+       "      <td>0.894070</td>\n",
+       "      <td>0.864369</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.880774</td>\n",
+       "      <td>0.890553</td>\n",
+       "      <td>0.900091</td>\n",
+       "      <td>0.893645</td>\n",
+       "      <td>0.878658</td>\n",
+       "      <td>0.886723</td>\n",
+       "      <td>0.898297</td>\n",
+       "      <td>0.876115</td>\n",
+       "      <td>0.881185</td>\n",
+       "      <td>0.874934</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730295</th>\n",
+       "      <td>cg06272054</td>\n",
+       "      <td>0.017587</td>\n",
+       "      <td>0.011651</td>\n",
+       "      <td>0.007993</td>\n",
+       "      <td>0.016188</td>\n",
+       "      <td>0.014288</td>\n",
+       "      <td>0.000261</td>\n",
+       "      <td>0.011462</td>\n",
+       "      <td>0.012948</td>\n",
+       "      <td>0.008948</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.016525</td>\n",
+       "      <td>0.015779</td>\n",
+       "      <td>0.023584</td>\n",
+       "      <td>0.014677</td>\n",
+       "      <td>0.008968</td>\n",
+       "      <td>0.005719</td>\n",
+       "      <td>0.008481</td>\n",
+       "      <td>0.009276</td>\n",
+       "      <td>0.016865</td>\n",
+       "      <td>0.016004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730296</th>\n",
+       "      <td>cg07255356</td>\n",
+       "      <td>0.020057</td>\n",
+       "      <td>0.019063</td>\n",
+       "      <td>0.024812</td>\n",
+       "      <td>0.025776</td>\n",
+       "      <td>0.030528</td>\n",
+       "      <td>0.024580</td>\n",
+       "      <td>0.019338</td>\n",
+       "      <td>0.027820</td>\n",
+       "      <td>0.021167</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.022855</td>\n",
+       "      <td>0.027397</td>\n",
+       "      <td>0.033744</td>\n",
+       "      <td>0.018661</td>\n",
+       "      <td>0.011457</td>\n",
+       "      <td>0.011255</td>\n",
+       "      <td>0.023139</td>\n",
+       "      <td>0.020177</td>\n",
+       "      <td>0.014928</td>\n",
+       "      <td>0.022536</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730297</th>\n",
+       "      <td>cg24220897</td>\n",
+       "      <td>0.901599</td>\n",
+       "      <td>0.894674</td>\n",
+       "      <td>0.934178</td>\n",
+       "      <td>0.946410</td>\n",
+       "      <td>0.936924</td>\n",
+       "      <td>0.950909</td>\n",
+       "      <td>0.934924</td>\n",
+       "      <td>0.915440</td>\n",
+       "      <td>0.928410</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.908163</td>\n",
+       "      <td>0.923211</td>\n",
+       "      <td>0.940120</td>\n",
+       "      <td>0.940749</td>\n",
+       "      <td>0.945274</td>\n",
+       "      <td>0.963318</td>\n",
+       "      <td>0.948381</td>\n",
+       "      <td>0.951894</td>\n",
+       "      <td>0.860762</td>\n",
+       "      <td>0.892109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730298</th>\n",
+       "      <td>cg12325588</td>\n",
+       "      <td>0.014632</td>\n",
+       "      <td>0.015572</td>\n",
+       "      <td>0.021971</td>\n",
+       "      <td>0.024834</td>\n",
+       "      <td>0.017136</td>\n",
+       "      <td>0.009834</td>\n",
+       "      <td>0.014974</td>\n",
+       "      <td>0.018213</td>\n",
+       "      <td>0.013185</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.012493</td>\n",
+       "      <td>0.022852</td>\n",
+       "      <td>0.021591</td>\n",
+       "      <td>0.011124</td>\n",
+       "      <td>0.005157</td>\n",
+       "      <td>0.011635</td>\n",
+       "      <td>0.012188</td>\n",
+       "      <td>0.008102</td>\n",
+       "      <td>0.027524</td>\n",
+       "      <td>0.019300</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>730299 rows × 419 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unnamed: 0     461_x     487_y     325_x     333_x     417_x  \\\n",
+       "0       cg07881041  0.936964  0.949428  0.931867  0.927504  0.940876   \n",
+       "1       cg03513874  0.962719  0.952201  0.934461  0.935450  0.953576   \n",
+       "2       cg05451842  0.025680  0.029857  0.021494  0.042652  0.036531   \n",
+       "3       cg14797042  0.962476  0.981526  0.970098  0.978789  0.974692   \n",
+       "4       cg09838562  0.017029  0.017377  0.022906  0.021399  0.029693   \n",
+       "...            ...       ...       ...       ...       ...       ...   \n",
+       "730294  cg19812938  0.872371  0.887197  0.894871  0.902936  0.875369   \n",
+       "730295  cg06272054  0.017587  0.011651  0.007993  0.016188  0.014288   \n",
+       "730296  cg07255356  0.020057  0.019063  0.024812  0.025776  0.030528   \n",
+       "730297  cg24220897  0.901599  0.894674  0.934178  0.946410  0.936924   \n",
+       "730298  cg12325588  0.014632  0.015572  0.021971  0.024834  0.017136   \n",
+       "\n",
+       "           355_x     373_y     329_y     503_x  ...      61_x     171_x  \\\n",
+       "0       0.935068  0.943885  0.941341  0.931477  ...  0.942243  0.945263   \n",
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+       "4       0.014263  0.020167  0.013235  0.014649  ...  0.012646  0.016793   \n",
+       "...          ...       ...       ...       ...  ...       ...       ...   \n",
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+       "730298  0.009834  0.014974  0.018213  0.013185  ...  0.012493  0.022852   \n",
+       "\n",
+       "           179_x     131_y      51_y      39_y     151_y     225_x      85_y  \\\n",
+       "0       0.935765  0.945791  0.944968  0.946432  0.939040  0.947915  0.925148   \n",
+       "1       0.944159  0.964771  0.951581  0.956153  0.959771  0.968014  0.938931   \n",
+       "2       0.034699  0.025350  0.024445  0.027273  0.025966  0.024816  0.050523   \n",
+       "3       0.975634  0.979691  0.987620  0.973312  0.973261  0.976011  0.973731   \n",
+       "4       0.025278  0.015261  0.003984  0.008068  0.011514  0.012520  0.021304   \n",
+       "...          ...       ...       ...       ...       ...       ...       ...   \n",
+       "730294  0.900091  0.893645  0.878658  0.886723  0.898297  0.876115  0.881185   \n",
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+       "730296  0.033744  0.018661  0.011457  0.011255  0.023139  0.020177  0.014928   \n",
+       "730297  0.940120  0.940749  0.945274  0.963318  0.948381  0.951894  0.860762   \n",
+       "730298  0.021591  0.011124  0.005157  0.011635  0.012188  0.008102  0.027524   \n",
+       "\n",
+       "           199_x  \n",
+       "0       0.908973  \n",
+       "1       0.946057  \n",
+       "2       0.031266  \n",
+       "3       0.961352  \n",
+       "4       0.027372  \n",
+       "...          ...  \n",
+       "730294  0.874934  \n",
+       "730295  0.016004  \n",
+       "730296  0.022536  \n",
+       "730297  0.892109  \n",
+       "730298  0.019300  \n",
+       "\n",
+       "[730299 rows x 419 columns]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_train_csv = X_train_sorted.drop(columns=[\"label\"])\n",
+    "\n",
+    "X_train_csv = pd.concat([ df_beta[\"Unnamed: 0\"], X_train_csv.T], axis=1)\n",
+    "X_train_csv.to_csv(\"result/GSE243529_aba/X_train_sorted_0.8.csv\",index=False)\n",
+    "X_train_csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <th></th>\n",
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+       "      <th>403_x</th>\n",
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+       "      <th>0</th>\n",
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+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg03513874</td>\n",
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+       "      <td>0.949377</td>\n",
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+       "      <td>0.952016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg05451842</td>\n",
+       "      <td>0.030578</td>\n",
+       "      <td>0.044631</td>\n",
+       "      <td>0.028441</td>\n",
+       "      <td>0.028637</td>\n",
+       "      <td>0.047084</td>\n",
+       "      <td>0.030067</td>\n",
+       "      <td>0.039009</td>\n",
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+       "      <td>0.030951</td>\n",
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+       "      <td>0.021382</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg14797042</td>\n",
+       "      <td>0.961247</td>\n",
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+       "      <td>0.975811</td>\n",
+       "      <td>0.983298</td>\n",
+       "      <td>0.986134</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg09838562</td>\n",
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+       "    <tr>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730295</th>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730296</th>\n",
+       "      <td>cg07255356</td>\n",
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+       "      <td>0.022010</td>\n",
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+       "    <tr>\n",
+       "      <th>730297</th>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730298</th>\n",
+       "      <td>cg12325588</td>\n",
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+       "      <td>0.015008</td>\n",
+       "      <td>0.008226</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>730299 rows × 106 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unnamed: 0     403_x     435_x     293_x     393_x     275_x  \\\n",
+       "0       cg07881041  0.925396  0.947303  0.938954  0.939975  0.922442   \n",
+       "1       cg03513874  0.933164  0.944911  0.956221  0.948010  0.944239   \n",
+       "2       cg05451842  0.030578  0.044631  0.028441  0.028637  0.047084   \n",
+       "3       cg14797042  0.961247  0.974482  0.980708  0.975787  0.970141   \n",
+       "4       cg09838562  0.032200  0.023581  0.013423  0.010973  0.026229   \n",
+       "...            ...       ...       ...       ...       ...       ...   \n",
+       "730294  cg19812938  0.852815  0.903333  0.897762  0.885246  0.874131   \n",
+       "730295  cg06272054  0.016953  0.024717  0.009095  0.014341  0.013413   \n",
+       "730296  cg07255356  0.038007  0.035257  0.022010  0.025008  0.033487   \n",
+       "730297  cg24220897  0.898344  0.938714  0.939835  0.900901  0.900720   \n",
+       "730298  cg12325588  0.041863  0.019065  0.012027  0.019712  0.029354   \n",
+       "\n",
+       "           415_x     459_x     465_x     287_y  ...     233_y     169_x  \\\n",
+       "0       0.949439  0.939303  0.937067  0.931057  ...  0.947827  0.937246   \n",
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+       "2       0.030067  0.039009  0.046011  0.030951  ...  0.020006  0.026890   \n",
+       "3       0.964899  0.983623  0.983232  0.980500  ...  0.982913  0.901677   \n",
+       "4       0.017895  0.023379  0.025863  0.010268  ...  0.016572  0.021044   \n",
+       "...          ...       ...       ...       ...  ...       ...       ...   \n",
+       "730294  0.867878  0.867081  0.879954  0.883569  ...  0.887307  0.882253   \n",
+       "730295  0.013033  0.022802  0.013771  0.008347  ...  0.012788  0.016233   \n",
+       "730296  0.028528  0.029784  0.020412  0.012821  ...  0.021808  0.028165   \n",
+       "730297  0.915928  0.909081  0.921105  0.929455  ...  0.921987  0.892495   \n",
+       "730298  0.022630  0.028294  0.018776  0.013149  ...  0.012588  0.010753   \n",
+       "\n",
+       "           153_x      93_x     129_y       201       1_y      29_x      87_x  \\\n",
+       "0       0.933927  0.947029  0.953174  0.961602  0.944083  0.926923  0.921947   \n",
+       "1       0.934190  0.953934  0.942626  0.982256  0.943296  0.949377  0.953743   \n",
+       "2       0.035600  0.019264  0.025369  0.034629  0.012583  0.034615  0.034204   \n",
+       "3       0.979260  0.977294  0.986977  0.979132  0.989079  0.975811  0.983298   \n",
+       "4       0.016859  0.014087  0.010863  0.017423  0.009669  0.017060  0.022228   \n",
+       "...          ...       ...       ...       ...       ...       ...       ...   \n",
+       "730294  0.872711  0.884156  0.873584  0.868828  0.881670  0.902775  0.889348   \n",
+       "730295  0.007149  0.017309  0.009625  0.008354  0.008530  0.011138  0.016300   \n",
+       "730296  0.023740  0.026254  0.011387  0.023185  0.013267  0.025480  0.025727   \n",
+       "730297  0.919380  0.931818  0.862911  0.958349  0.934471  0.943655  0.919963   \n",
+       "730298  0.029669  0.007427  0.012501  0.012981  0.009191  0.005422  0.015008   \n",
+       "\n",
+       "            39_x  \n",
+       "0       0.969780  \n",
+       "1       0.952016  \n",
+       "2       0.021382  \n",
+       "3       0.986134  \n",
+       "4       0.007662  \n",
+       "...          ...  \n",
+       "730294  0.879664  \n",
+       "730295  0.004846  \n",
+       "730296  0.011394  \n",
+       "730297  0.943813  \n",
+       "730298  0.008226  \n",
+       "\n",
+       "[730299 rows x 106 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_test_csv = X_test_sorted.drop(columns=[\"label\"])\n",
+    "\n",
+    "\n",
+    "X_test_csv = pd.concat([ df_beta[\"Unnamed: 0\"], X_test_csv.T], axis=1)\n",
+    "X_test_csv.to_csv(\"result/GSE243529_aba/X_test_sorted_0.2.csv\",index=False)\n",
+    "X_test_csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def IQR(df):\n",
+    "    Q1 = df.quantile(0.25)\n",
+    "    Q3 = df.quantile(0.75)\n",
+    "    IQR = Q3 - Q1\n",
+    "    upper_fence = Q3 + IQR*1.5\n",
+    "    lower_fence = Q1 - IQR*1.5\n",
+    "    return upper_fence,lower_fence\n",
+    "def no_outlier(df):\n",
+    "    upper_fence, lower_fence = IQR(df)\n",
+    "    ddf=df[(df>lower_fence)&(df<upper_fence)]\n",
+    "    return ddf\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
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+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>730289</th>\n",
+       "      <th>730290</th>\n",
+       "      <th>730291</th>\n",
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+       "      <th>730294</th>\n",
+       "      <th>730295</th>\n",
+       "      <th>730296</th>\n",
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+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>461_x</th>\n",
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+       "      <td>0.872371</td>\n",
+       "      <td>0.017587</td>\n",
+       "      <td>0.020057</td>\n",
+       "      <td>0.901599</td>\n",
+       "      <td>0.014632</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>487_y</th>\n",
+       "      <td>0.949428</td>\n",
+       "      <td>0.952201</td>\n",
+       "      <td>0.029857</td>\n",
+       "      <td>0.981526</td>\n",
+       "      <td>0.017377</td>\n",
+       "      <td>0.959861</td>\n",
+       "      <td>0.715194</td>\n",
+       "      <td>0.867854</td>\n",
+       "      <td>0.605377</td>\n",
+       "      <td>0.562242</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.017352</td>\n",
+       "      <td>0.915497</td>\n",
+       "      <td>0.919045</td>\n",
+       "      <td>0.945706</td>\n",
+       "      <td>0.838562</td>\n",
+       "      <td>0.887197</td>\n",
+       "      <td>0.011651</td>\n",
+       "      <td>0.019063</td>\n",
+       "      <td>0.894674</td>\n",
+       "      <td>0.015572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>325_x</th>\n",
+       "      <td>0.931867</td>\n",
+       "      <td>0.934461</td>\n",
+       "      <td>0.021494</td>\n",
+       "      <td>0.970098</td>\n",
+       "      <td>0.022906</td>\n",
+       "      <td>0.957312</td>\n",
+       "      <td>0.661996</td>\n",
+       "      <td>0.908578</td>\n",
+       "      <td>0.546883</td>\n",
+       "      <td>0.603278</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.017268</td>\n",
+       "      <td>0.913535</td>\n",
+       "      <td>0.921482</td>\n",
+       "      <td>0.939648</td>\n",
+       "      <td>0.893498</td>\n",
+       "      <td>0.894871</td>\n",
+       "      <td>0.007993</td>\n",
+       "      <td>0.024812</td>\n",
+       "      <td>0.934178</td>\n",
+       "      <td>0.021971</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>333_x</th>\n",
+       "      <td>0.927504</td>\n",
+       "      <td>0.935450</td>\n",
+       "      <td>0.042652</td>\n",
+       "      <td>0.978789</td>\n",
+       "      <td>0.021399</td>\n",
+       "      <td>0.962458</td>\n",
+       "      <td>0.663041</td>\n",
+       "      <td>0.863556</td>\n",
+       "      <td>0.604382</td>\n",
+       "      <td>0.611538</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.007489</td>\n",
+       "      <td>0.920278</td>\n",
+       "      <td>0.920077</td>\n",
+       "      <td>0.956543</td>\n",
+       "      <td>0.864772</td>\n",
+       "      <td>0.902936</td>\n",
+       "      <td>0.016188</td>\n",
+       "      <td>0.025776</td>\n",
+       "      <td>0.946410</td>\n",
+       "      <td>0.024834</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>417_x</th>\n",
+       "      <td>0.940876</td>\n",
+       "      <td>0.953576</td>\n",
+       "      <td>0.036531</td>\n",
+       "      <td>0.974692</td>\n",
+       "      <td>0.029693</td>\n",
+       "      <td>0.967838</td>\n",
+       "      <td>0.615006</td>\n",
+       "      <td>0.829632</td>\n",
+       "      <td>0.553901</td>\n",
+       "      <td>0.608524</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.010581</td>\n",
+       "      <td>0.895036</td>\n",
+       "      <td>0.908582</td>\n",
+       "      <td>0.941502</td>\n",
+       "      <td>0.869474</td>\n",
+       "      <td>0.875369</td>\n",
+       "      <td>0.014288</td>\n",
+       "      <td>0.030528</td>\n",
+       "      <td>0.936924</td>\n",
+       "      <td>0.017136</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>353_x</th>\n",
+       "      <td>0.939608</td>\n",
+       "      <td>0.956300</td>\n",
+       "      <td>0.025230</td>\n",
+       "      <td>0.986075</td>\n",
+       "      <td>0.004163</td>\n",
+       "      <td>0.959706</td>\n",
+       "      <td>0.663423</td>\n",
+       "      <td>0.905650</td>\n",
+       "      <td>0.548668</td>\n",
+       "      <td>0.602290</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.006933</td>\n",
+       "      <td>0.904147</td>\n",
+       "      <td>0.919035</td>\n",
+       "      <td>0.964416</td>\n",
+       "      <td>0.830813</td>\n",
+       "      <td>0.868742</td>\n",
+       "      <td>0.008068</td>\n",
+       "      <td>0.015873</td>\n",
+       "      <td>0.944329</td>\n",
+       "      <td>0.009715</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>463_y</th>\n",
+       "      <td>0.940137</td>\n",
+       "      <td>0.959091</td>\n",
+       "      <td>0.041088</td>\n",
+       "      <td>0.978323</td>\n",
+       "      <td>0.024030</td>\n",
+       "      <td>0.970832</td>\n",
+       "      <td>0.673075</td>\n",
+       "      <td>0.915203</td>\n",
+       "      <td>0.620670</td>\n",
+       "      <td>0.697394</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.018060</td>\n",
+       "      <td>0.897237</td>\n",
+       "      <td>0.944738</td>\n",
+       "      <td>0.953172</td>\n",
+       "      <td>0.848053</td>\n",
+       "      <td>0.874114</td>\n",
+       "      <td>0.018687</td>\n",
+       "      <td>0.029944</td>\n",
+       "      <td>0.927729</td>\n",
+       "      <td>0.019857</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>373_x</th>\n",
+       "      <td>0.923098</td>\n",
+       "      <td>0.962200</td>\n",
+       "      <td>0.037159</td>\n",
+       "      <td>0.985993</td>\n",
+       "      <td>0.021640</td>\n",
+       "      <td>0.949598</td>\n",
+       "      <td>0.655550</td>\n",
+       "      <td>0.819240</td>\n",
+       "      <td>0.494561</td>\n",
+       "      <td>0.452911</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.013562</td>\n",
+       "      <td>0.899184</td>\n",
+       "      <td>0.897051</td>\n",
+       "      <td>0.948760</td>\n",
+       "      <td>0.894075</td>\n",
+       "      <td>0.876227</td>\n",
+       "      <td>0.013828</td>\n",
+       "      <td>0.019009</td>\n",
+       "      <td>0.949025</td>\n",
+       "      <td>0.021670</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>403_y</th>\n",
+       "      <td>0.939541</td>\n",
+       "      <td>0.960439</td>\n",
+       "      <td>0.025340</td>\n",
+       "      <td>0.983061</td>\n",
+       "      <td>0.009096</td>\n",
+       "      <td>0.964133</td>\n",
+       "      <td>0.713938</td>\n",
+       "      <td>0.887766</td>\n",
+       "      <td>0.582812</td>\n",
+       "      <td>0.592028</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.010505</td>\n",
+       "      <td>0.915440</td>\n",
+       "      <td>0.935758</td>\n",
+       "      <td>0.964990</td>\n",
+       "      <td>0.865723</td>\n",
+       "      <td>0.885989</td>\n",
+       "      <td>0.008309</td>\n",
+       "      <td>0.017102</td>\n",
+       "      <td>0.952502</td>\n",
+       "      <td>0.016356</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>331_x</th>\n",
+       "      <td>0.932438</td>\n",
+       "      <td>0.950053</td>\n",
+       "      <td>0.033868</td>\n",
+       "      <td>0.972809</td>\n",
+       "      <td>0.011918</td>\n",
+       "      <td>0.952333</td>\n",
+       "      <td>0.667032</td>\n",
+       "      <td>0.878773</td>\n",
+       "      <td>0.638533</td>\n",
+       "      <td>0.683002</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014666</td>\n",
+       "      <td>0.897305</td>\n",
+       "      <td>0.923025</td>\n",
+       "      <td>0.938739</td>\n",
+       "      <td>0.856873</td>\n",
+       "      <td>0.893405</td>\n",
+       "      <td>0.014508</td>\n",
+       "      <td>0.032013</td>\n",
+       "      <td>0.926020</td>\n",
+       "      <td>0.012699</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>210 rows × 730299 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         0         1         2         3         4         5         6       \\\n",
+       "461_x  0.936964  0.962719  0.025680  0.962476  0.017029  0.951755  0.697616   \n",
+       "487_y  0.949428  0.952201  0.029857  0.981526  0.017377  0.959861  0.715194   \n",
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+       "333_x  0.927504  0.935450  0.042652  0.978789  0.021399  0.962458  0.663041   \n",
+       "417_x  0.940876  0.953576  0.036531  0.974692  0.029693  0.967838  0.615006   \n",
+       "...         ...       ...       ...       ...       ...       ...       ...   \n",
+       "353_x  0.939608  0.956300  0.025230  0.986075  0.004163  0.959706  0.663423   \n",
+       "463_y  0.940137  0.959091  0.041088  0.978323  0.024030  0.970832  0.673075   \n",
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+       "403_y  0.939541  0.960439  0.025340  0.983061  0.009096  0.964133  0.713938   \n",
+       "331_x  0.932438  0.950053  0.033868  0.972809  0.011918  0.952333  0.667032   \n",
+       "\n",
+       "         7         8         9       ...    730289    730290    730291  \\\n",
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+       "325_x  0.908578  0.546883  0.603278  ...  0.017268  0.913535  0.921482   \n",
+       "333_x  0.863556  0.604382  0.611538  ...  0.007489  0.920278  0.920077   \n",
+       "417_x  0.829632  0.553901  0.608524  ...  0.010581  0.895036  0.908582   \n",
+       "...         ...       ...       ...  ...       ...       ...       ...   \n",
+       "353_x  0.905650  0.548668  0.602290  ...  0.006933  0.904147  0.919035   \n",
+       "463_y  0.915203  0.620670  0.697394  ...  0.018060  0.897237  0.944738   \n",
+       "373_x  0.819240  0.494561  0.452911  ...  0.013562  0.899184  0.897051   \n",
+       "403_y  0.887766  0.582812  0.592028  ...  0.010505  0.915440  0.935758   \n",
+       "331_x  0.878773  0.638533  0.683002  ...  0.014666  0.897305  0.923025   \n",
+       "\n",
+       "         730292    730293    730294    730295    730296    730297    730298  \n",
+       "461_x  0.957935  0.865365  0.872371  0.017587  0.020057  0.901599  0.014632  \n",
+       "487_y  0.945706  0.838562  0.887197  0.011651  0.019063  0.894674  0.015572  \n",
+       "325_x  0.939648  0.893498  0.894871  0.007993  0.024812  0.934178  0.021971  \n",
+       "333_x  0.956543  0.864772  0.902936  0.016188  0.025776  0.946410  0.024834  \n",
+       "417_x  0.941502  0.869474  0.875369  0.014288  0.030528  0.936924  0.017136  \n",
+       "...         ...       ...       ...       ...       ...       ...       ...  \n",
+       "353_x  0.964416  0.830813  0.868742  0.008068  0.015873  0.944329  0.009715  \n",
+       "463_y  0.953172  0.848053  0.874114  0.018687  0.029944  0.927729  0.019857  \n",
+       "373_x  0.948760  0.894075  0.876227  0.013828  0.019009  0.949025  0.021670  \n",
+       "403_y  0.964990  0.865723  0.885989  0.008309  0.017102  0.952502  0.016356  \n",
+       "331_x  0.938739  0.856873  0.893405  0.014508  0.032013  0.926020  0.012699  \n",
+       "\n",
+       "[210 rows x 730299 columns]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "k = train_tumor\n",
+    "kk = train_normal\n",
+    "\n",
+    "train_normal"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "all_beta_normalized_normal = no_outlier(train_normal)\n",
+    "all_beta_normalized_tumor = no_outlier(train_tumor)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <td>0.978634</td>\n",
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+       "      <td>0.009770</td>\n",
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+       "      <td>0.007360</td>\n",
+       "      <td>0.023650</td>\n",
+       "      <td>0.919170</td>\n",
+       "      <td>0.005686</td>\n",
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+       "      <th>3_x</th>\n",
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+       "      <td>0.935187</td>\n",
+       "      <td>0.022880</td>\n",
+       "      <td>0.989621</td>\n",
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+       "      <td>0.903661</td>\n",
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+       "      <td>0.016949</td>\n",
+       "      <td>0.921312</td>\n",
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+       "      <td>0.037748</td>\n",
+       "      <td>0.943066</td>\n",
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+       "      <td>0.956153</td>\n",
+       "      <td>0.027273</td>\n",
+       "      <td>0.973312</td>\n",
+       "      <td>0.008068</td>\n",
+       "      <td>0.972754</td>\n",
+       "      <td>0.635796</td>\n",
+       "      <td>0.885358</td>\n",
+       "      <td>0.547771</td>\n",
+       "      <td>0.616187</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.007876</td>\n",
+       "      <td>0.905825</td>\n",
+       "      <td>0.927869</td>\n",
+       "      <td>0.954496</td>\n",
+       "      <td>0.898807</td>\n",
+       "      <td>0.886723</td>\n",
+       "      <td>0.005719</td>\n",
+       "      <td>0.011255</td>\n",
+       "      <td>0.963318</td>\n",
+       "      <td>0.011635</td>\n",
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+       "      <td>0.703383</td>\n",
+       "      <td>0.732262</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.012993</td>\n",
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+       "      <td>0.933197</td>\n",
+       "      <td>0.967027</td>\n",
+       "      <td>0.948662</td>\n",
+       "      <td>0.898297</td>\n",
+       "      <td>0.008481</td>\n",
+       "      <td>0.023139</td>\n",
+       "      <td>0.948381</td>\n",
+       "      <td>0.012188</td>\n",
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+       "    <tr>\n",
+       "      <th>225_x</th>\n",
+       "      <td>0.947915</td>\n",
+       "      <td>0.968014</td>\n",
+       "      <td>0.024816</td>\n",
+       "      <td>0.976011</td>\n",
+       "      <td>0.012520</td>\n",
+       "      <td>0.973932</td>\n",
+       "      <td>0.647734</td>\n",
+       "      <td>0.911690</td>\n",
+       "      <td>0.599466</td>\n",
+       "      <td>0.567957</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014621</td>\n",
+       "      <td>0.896927</td>\n",
+       "      <td>0.934178</td>\n",
+       "      <td>0.957408</td>\n",
+       "      <td>0.828406</td>\n",
+       "      <td>0.876115</td>\n",
+       "      <td>0.009276</td>\n",
+       "      <td>0.020177</td>\n",
+       "      <td>0.951894</td>\n",
+       "      <td>0.008102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>85_y</th>\n",
+       "      <td>0.925148</td>\n",
+       "      <td>0.938931</td>\n",
+       "      <td>0.050523</td>\n",
+       "      <td>0.973731</td>\n",
+       "      <td>0.021304</td>\n",
+       "      <td>0.946569</td>\n",
+       "      <td>0.672242</td>\n",
+       "      <td>0.891835</td>\n",
+       "      <td>0.619501</td>\n",
+       "      <td>0.564449</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.023434</td>\n",
+       "      <td>0.909421</td>\n",
+       "      <td>0.922070</td>\n",
+       "      <td>0.942739</td>\n",
+       "      <td>0.851190</td>\n",
+       "      <td>0.881185</td>\n",
+       "      <td>0.016865</td>\n",
+       "      <td>0.014928</td>\n",
+       "      <td>0.860762</td>\n",
+       "      <td>0.027524</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>199_x</th>\n",
+       "      <td>0.908973</td>\n",
+       "      <td>0.946057</td>\n",
+       "      <td>0.031266</td>\n",
+       "      <td>0.961352</td>\n",
+       "      <td>0.027372</td>\n",
+       "      <td>0.969311</td>\n",
+       "      <td>0.633144</td>\n",
+       "      <td>0.961896</td>\n",
+       "      <td>0.763399</td>\n",
+       "      <td>0.842941</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.012999</td>\n",
+       "      <td>0.885016</td>\n",
+       "      <td>0.898517</td>\n",
+       "      <td>0.955516</td>\n",
+       "      <td>0.478584</td>\n",
+       "      <td>0.874934</td>\n",
+       "      <td>0.016004</td>\n",
+       "      <td>0.022536</td>\n",
+       "      <td>0.892109</td>\n",
+       "      <td>0.019300</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>208 rows × 730299 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         0         1         2         3         4         5         6       \\\n",
+       "253_x  0.932493  0.947340  0.036287  0.975147  0.016267  0.959567  0.631247   \n",
+       "125_y  0.939642  0.954746  0.037745  0.960692  0.022165  0.961634  0.616871   \n",
+       "247_x  0.963177  0.950974  0.047110  0.978634  0.012414  0.948015  0.692950   \n",
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+       "215_y  0.957730  0.959237  0.027434  0.972297  0.017713  0.966196  0.743326   \n",
+       "...         ...       ...       ...       ...       ...       ...       ...   \n",
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+       "85_y   0.925148  0.938931  0.050523  0.973731  0.021304  0.946569  0.672242   \n",
+       "199_x  0.908973  0.946057  0.031266  0.961352  0.027372  0.969311  0.633144   \n",
+       "\n",
+       "         7         8         9       ...    730289    730290    730291  \\\n",
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+       "3_x    0.854900  0.529452  0.575943  ...  0.013298  0.914774  0.939838   \n",
+       "215_y  0.848918  0.510969  0.658933  ...  0.017939  0.882241  0.939298   \n",
+       "...         ...       ...       ...  ...       ...       ...       ...   \n",
+       "39_y   0.885358  0.547771  0.616187  ...  0.007876  0.905825  0.927869   \n",
+       "151_y  0.910429  0.703383  0.732262  ...  0.012993  0.923133  0.933197   \n",
+       "225_x  0.911690  0.599466  0.567957  ...  0.014621  0.896927  0.934178   \n",
+       "85_y   0.891835  0.619501  0.564449  ...  0.023434  0.909421  0.922070   \n",
+       "199_x  0.961896  0.763399  0.842941  ...  0.012999  0.885016  0.898517   \n",
+       "\n",
+       "         730292    730293    730294    730295    730296    730297    730298  \n",
+       "253_x  0.949632  0.849505  0.879413  0.008597  0.025104  0.934250  0.021318  \n",
+       "125_y  0.932029  0.884060  0.863933  0.011173  0.032682  0.941942  0.040035  \n",
+       "247_x  0.935785  0.892077  0.884135  0.007360  0.023650  0.919170  0.005686  \n",
+       "3_x    0.961787  0.914687  0.903661  0.011305  0.016949  0.921312  0.006455  \n",
+       "215_y  0.958313  0.897394  0.879969  0.017862  0.037748  0.943066  0.017803  \n",
+       "...         ...       ...       ...       ...       ...       ...       ...  \n",
+       "39_y   0.954496  0.898807  0.886723  0.005719  0.011255  0.963318  0.011635  \n",
+       "151_y  0.967027  0.948662  0.898297  0.008481  0.023139  0.948381  0.012188  \n",
+       "225_x  0.957408  0.828406  0.876115  0.009276  0.020177  0.951894  0.008102  \n",
+       "85_y   0.942739  0.851190  0.881185  0.016865  0.014928  0.860762  0.027524  \n",
+       "199_x  0.955516  0.478584  0.874934  0.016004  0.022536  0.892109  0.019300  \n",
+       "\n",
+       "[208 rows x 730299 columns]"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_tumor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0         0.938926\n",
+       "1         0.952476\n",
+       "2         0.032351\n",
+       "3         0.974024\n",
+       "4         0.018999\n",
+       "            ...   \n",
+       "730294    0.881875\n",
+       "730295    0.014691\n",
+       "730296    0.025056\n",
+       "730297    0.921886\n",
+       "730298    0.018928\n",
+       "Length: 730299, dtype: float64"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_normal_avg = train_normal.mean(skipna=True, axis = 0)\n",
+    "train_normal_avg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>730289</th>\n",
+       "      <th>730290</th>\n",
+       "      <th>730291</th>\n",
+       "      <th>730292</th>\n",
+       "      <th>730293</th>\n",
+       "      <th>730294</th>\n",
+       "      <th>730295</th>\n",
+       "      <th>730296</th>\n",
+       "      <th>730297</th>\n",
+       "      <th>730298</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>253_x</th>\n",
+       "      <td>-0.006434</td>\n",
+       "      <td>-0.005135</td>\n",
+       "      <td>0.003936</td>\n",
+       "      <td>0.001123</td>\n",
+       "      <td>-0.002732</td>\n",
+       "      <td>-0.001861</td>\n",
+       "      <td>-0.021329</td>\n",
+       "      <td>-0.037894</td>\n",
+       "      <td>-0.005184</td>\n",
+       "      <td>-0.033538</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000557</td>\n",
+       "      <td>-0.007762</td>\n",
+       "      <td>-0.012392</td>\n",
+       "      <td>0.002060</td>\n",
+       "      <td>-0.003150</td>\n",
+       "      <td>-0.002462</td>\n",
+       "      <td>-0.006094</td>\n",
+       "      <td>0.000048</td>\n",
+       "      <td>0.012364</td>\n",
+       "      <td>0.002390</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125_y</th>\n",
+       "      <td>0.000716</td>\n",
+       "      <td>0.002270</td>\n",
+       "      <td>0.005394</td>\n",
+       "      <td>-0.013332</td>\n",
+       "      <td>0.003166</td>\n",
+       "      <td>0.000206</td>\n",
+       "      <td>-0.035705</td>\n",
+       "      <td>-0.016508</td>\n",
+       "      <td>-0.048848</td>\n",
+       "      <td>-0.049963</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.003380</td>\n",
+       "      <td>-0.021147</td>\n",
+       "      <td>-0.012083</td>\n",
+       "      <td>-0.015543</td>\n",
+       "      <td>0.031404</td>\n",
+       "      <td>-0.017942</td>\n",
+       "      <td>-0.003518</td>\n",
+       "      <td>0.007626</td>\n",
+       "      <td>0.020056</td>\n",
+       "      <td>0.021108</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>247_x</th>\n",
+       "      <td>0.024251</td>\n",
+       "      <td>-0.001501</td>\n",
+       "      <td>0.014759</td>\n",
+       "      <td>0.004610</td>\n",
+       "      <td>-0.006585</td>\n",
+       "      <td>-0.013413</td>\n",
+       "      <td>0.040374</td>\n",
+       "      <td>0.000685</td>\n",
+       "      <td>0.022424</td>\n",
+       "      <td>-0.022499</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.006246</td>\n",
+       "      <td>-0.006019</td>\n",
+       "      <td>-0.006536</td>\n",
+       "      <td>-0.011786</td>\n",
+       "      <td>0.039422</td>\n",
+       "      <td>0.002260</td>\n",
+       "      <td>-0.007331</td>\n",
+       "      <td>-0.001406</td>\n",
+       "      <td>-0.002716</td>\n",
+       "      <td>-0.013242</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3_x</th>\n",
+       "      <td>-0.006860</td>\n",
+       "      <td>-0.017289</td>\n",
+       "      <td>-0.009471</td>\n",
+       "      <td>0.015597</td>\n",
+       "      <td>-0.009979</td>\n",
+       "      <td>0.006725</td>\n",
+       "      <td>-0.021784</td>\n",
+       "      <td>-0.020575</td>\n",
+       "      <td>-0.038415</td>\n",
+       "      <td>-0.011056</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.002718</td>\n",
+       "      <td>0.014274</td>\n",
+       "      <td>0.017862</td>\n",
+       "      <td>0.014215</td>\n",
+       "      <td>0.062032</td>\n",
+       "      <td>0.021786</td>\n",
+       "      <td>-0.003386</td>\n",
+       "      <td>-0.008107</td>\n",
+       "      <td>-0.000574</td>\n",
+       "      <td>-0.012473</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>215_y</th>\n",
+       "      <td>0.018804</td>\n",
+       "      <td>0.006761</td>\n",
+       "      <td>-0.004917</td>\n",
+       "      <td>-0.001727</td>\n",
+       "      <td>-0.001286</td>\n",
+       "      <td>0.004768</td>\n",
+       "      <td>0.090750</td>\n",
+       "      <td>-0.026557</td>\n",
+       "      <td>-0.056897</td>\n",
+       "      <td>0.071934</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.001923</td>\n",
+       "      <td>-0.018259</td>\n",
+       "      <td>0.017321</td>\n",
+       "      <td>0.010741</td>\n",
+       "      <td>0.044739</td>\n",
+       "      <td>-0.001906</td>\n",
+       "      <td>0.003171</td>\n",
+       "      <td>0.012691</td>\n",
+       "      <td>0.021180</td>\n",
+       "      <td>-0.001125</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39_y</th>\n",
+       "      <td>0.007506</td>\n",
+       "      <td>0.003677</td>\n",
+       "      <td>-0.005078</td>\n",
+       "      <td>-0.000712</td>\n",
+       "      <td>-0.010931</td>\n",
+       "      <td>0.011326</td>\n",
+       "      <td>-0.016780</td>\n",
+       "      <td>0.009883</td>\n",
+       "      <td>-0.020095</td>\n",
+       "      <td>0.029188</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.008140</td>\n",
+       "      <td>0.005325</td>\n",
+       "      <td>0.005893</td>\n",
+       "      <td>0.006924</td>\n",
+       "      <td>0.046151</td>\n",
+       "      <td>0.004848</td>\n",
+       "      <td>-0.008972</td>\n",
+       "      <td>-0.013802</td>\n",
+       "      <td>0.041432</td>\n",
+       "      <td>-0.007292</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>151_y</th>\n",
+       "      <td>0.000114</td>\n",
+       "      <td>0.007296</td>\n",
+       "      <td>-0.006385</td>\n",
+       "      <td>-0.000763</td>\n",
+       "      <td>-0.007485</td>\n",
+       "      <td>0.008225</td>\n",
+       "      <td>0.082326</td>\n",
+       "      <td>0.034954</td>\n",
+       "      <td>0.135517</td>\n",
+       "      <td>0.145262</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.003022</td>\n",
+       "      <td>0.022633</td>\n",
+       "      <td>0.011221</td>\n",
+       "      <td>0.019455</td>\n",
+       "      <td>0.096007</td>\n",
+       "      <td>0.016421</td>\n",
+       "      <td>-0.006210</td>\n",
+       "      <td>-0.001917</td>\n",
+       "      <td>0.026495</td>\n",
+       "      <td>-0.006740</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>225_x</th>\n",
+       "      <td>0.008989</td>\n",
+       "      <td>0.015538</td>\n",
+       "      <td>-0.007535</td>\n",
+       "      <td>0.001987</td>\n",
+       "      <td>-0.006479</td>\n",
+       "      <td>0.012505</td>\n",
+       "      <td>-0.004841</td>\n",
+       "      <td>0.036215</td>\n",
+       "      <td>0.031599</td>\n",
+       "      <td>-0.019043</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.001395</td>\n",
+       "      <td>-0.003572</td>\n",
+       "      <td>0.012202</td>\n",
+       "      <td>0.009836</td>\n",
+       "      <td>-0.024249</td>\n",
+       "      <td>-0.005761</td>\n",
+       "      <td>-0.005415</td>\n",
+       "      <td>-0.004879</td>\n",
+       "      <td>0.030008</td>\n",
+       "      <td>-0.010826</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>85_y</th>\n",
+       "      <td>-0.013778</td>\n",
+       "      <td>-0.013545</td>\n",
+       "      <td>0.018172</td>\n",
+       "      <td>-0.000293</td>\n",
+       "      <td>0.002305</td>\n",
+       "      <td>-0.014859</td>\n",
+       "      <td>0.019666</td>\n",
+       "      <td>0.016359</td>\n",
+       "      <td>0.051634</td>\n",
+       "      <td>-0.022551</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.007419</td>\n",
+       "      <td>0.008921</td>\n",
+       "      <td>0.000093</td>\n",
+       "      <td>-0.004833</td>\n",
+       "      <td>-0.001465</td>\n",
+       "      <td>-0.000690</td>\n",
+       "      <td>0.002174</td>\n",
+       "      <td>-0.010128</td>\n",
+       "      <td>-0.061124</td>\n",
+       "      <td>0.008596</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>199_x</th>\n",
+       "      <td>-0.029953</td>\n",
+       "      <td>-0.006419</td>\n",
+       "      <td>-0.001085</td>\n",
+       "      <td>-0.012671</td>\n",
+       "      <td>0.008373</td>\n",
+       "      <td>0.007883</td>\n",
+       "      <td>-0.019432</td>\n",
+       "      <td>0.086421</td>\n",
+       "      <td>0.195532</td>\n",
+       "      <td>0.255941</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.003016</td>\n",
+       "      <td>-0.015484</td>\n",
+       "      <td>-0.023460</td>\n",
+       "      <td>0.007944</td>\n",
+       "      <td>-0.374072</td>\n",
+       "      <td>-0.006941</td>\n",
+       "      <td>0.001313</td>\n",
+       "      <td>-0.002521</td>\n",
+       "      <td>-0.029777</td>\n",
+       "      <td>0.000372</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>208 rows × 730299 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         0         1         2         3         4         5         6       \\\n",
+       "253_x -0.006434 -0.005135  0.003936  0.001123 -0.002732 -0.001861 -0.021329   \n",
+       "125_y  0.000716  0.002270  0.005394 -0.013332  0.003166  0.000206 -0.035705   \n",
+       "247_x  0.024251 -0.001501  0.014759  0.004610 -0.006585 -0.013413  0.040374   \n",
+       "3_x   -0.006860 -0.017289 -0.009471  0.015597 -0.009979  0.006725 -0.021784   \n",
+       "215_y  0.018804  0.006761 -0.004917 -0.001727 -0.001286  0.004768  0.090750   \n",
+       "...         ...       ...       ...       ...       ...       ...       ...   \n",
+       "39_y   0.007506  0.003677 -0.005078 -0.000712 -0.010931  0.011326 -0.016780   \n",
+       "151_y  0.000114  0.007296 -0.006385 -0.000763 -0.007485  0.008225  0.082326   \n",
+       "225_x  0.008989  0.015538 -0.007535  0.001987 -0.006479  0.012505 -0.004841   \n",
+       "85_y  -0.013778 -0.013545  0.018172 -0.000293  0.002305 -0.014859  0.019666   \n",
+       "199_x -0.029953 -0.006419 -0.001085 -0.012671  0.008373  0.007883 -0.019432   \n",
+       "\n",
+       "         7         8         9       ...    730289    730290    730291  \\\n",
+       "253_x -0.037894 -0.005184 -0.033538  ...  0.000557 -0.007762 -0.012392   \n",
+       "125_y -0.016508 -0.048848 -0.049963  ...  0.003380 -0.021147 -0.012083   \n",
+       "247_x  0.000685  0.022424 -0.022499  ... -0.006246 -0.006019 -0.006536   \n",
+       "3_x   -0.020575 -0.038415 -0.011056  ... -0.002718  0.014274  0.017862   \n",
+       "215_y -0.026557 -0.056897  0.071934  ...  0.001923 -0.018259  0.017321   \n",
+       "...         ...       ...       ...  ...       ...       ...       ...   \n",
+       "39_y   0.009883 -0.020095  0.029188  ... -0.008140  0.005325  0.005893   \n",
+       "151_y  0.034954  0.135517  0.145262  ... -0.003022  0.022633  0.011221   \n",
+       "225_x  0.036215  0.031599 -0.019043  ... -0.001395 -0.003572  0.012202   \n",
+       "85_y   0.016359  0.051634 -0.022551  ...  0.007419  0.008921  0.000093   \n",
+       "199_x  0.086421  0.195532  0.255941  ... -0.003016 -0.015484 -0.023460   \n",
+       "\n",
+       "         730292    730293    730294    730295    730296    730297    730298  \n",
+       "253_x  0.002060 -0.003150 -0.002462 -0.006094  0.000048  0.012364  0.002390  \n",
+       "125_y -0.015543  0.031404 -0.017942 -0.003518  0.007626  0.020056  0.021108  \n",
+       "247_x -0.011786  0.039422  0.002260 -0.007331 -0.001406 -0.002716 -0.013242  \n",
+       "3_x    0.014215  0.062032  0.021786 -0.003386 -0.008107 -0.000574 -0.012473  \n",
+       "215_y  0.010741  0.044739 -0.001906  0.003171  0.012691  0.021180 -0.001125  \n",
+       "...         ...       ...       ...       ...       ...       ...       ...  \n",
+       "39_y   0.006924  0.046151  0.004848 -0.008972 -0.013802  0.041432 -0.007292  \n",
+       "151_y  0.019455  0.096007  0.016421 -0.006210 -0.001917  0.026495 -0.006740  \n",
+       "225_x  0.009836 -0.024249 -0.005761 -0.005415 -0.004879  0.030008 -0.010826  \n",
+       "85_y  -0.004833 -0.001465 -0.000690  0.002174 -0.010128 -0.061124  0.008596  \n",
+       "199_x  0.007944 -0.374072 -0.006941  0.001313 -0.002521 -0.029777  0.000372  \n",
+       "\n",
+       "[208 rows x 730299 columns]"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_tumor=(train_tumor).subtract(train_normal_avg, axis = 1)\n",
+    "train_tumor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
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+       "\n",
+       "    .dataframe thead th {\n",
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>730289</th>\n",
+       "      <th>730290</th>\n",
+       "      <th>730291</th>\n",
+       "      <th>730292</th>\n",
+       "      <th>730293</th>\n",
+       "      <th>730294</th>\n",
+       "      <th>730295</th>\n",
+       "      <th>730296</th>\n",
+       "      <th>730297</th>\n",
+       "      <th>730298</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>253_x</th>\n",
+       "      <td>-0.006434</td>\n",
+       "      <td>-0.005135</td>\n",
+       "      <td>0.003936</td>\n",
+       "      <td>0.001123</td>\n",
+       "      <td>-0.002732</td>\n",
+       "      <td>-0.001861</td>\n",
+       "      <td>-0.021329</td>\n",
+       "      <td>-0.037894</td>\n",
+       "      <td>-0.005184</td>\n",
+       "      <td>-0.033538</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000557</td>\n",
+       "      <td>-0.007762</td>\n",
+       "      <td>-0.012392</td>\n",
+       "      <td>0.002060</td>\n",
+       "      <td>-0.003150</td>\n",
+       "      <td>-0.002462</td>\n",
+       "      <td>-0.006094</td>\n",
+       "      <td>0.000048</td>\n",
+       "      <td>0.012364</td>\n",
+       "      <td>0.002390</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125_y</th>\n",
+       "      <td>0.000716</td>\n",
+       "      <td>0.002270</td>\n",
+       "      <td>0.005394</td>\n",
+       "      <td>-0.013332</td>\n",
+       "      <td>0.003166</td>\n",
+       "      <td>0.000206</td>\n",
+       "      <td>-0.035705</td>\n",
+       "      <td>-0.016508</td>\n",
+       "      <td>-0.048848</td>\n",
+       "      <td>-0.049963</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.003380</td>\n",
+       "      <td>-0.021147</td>\n",
+       "      <td>-0.012083</td>\n",
+       "      <td>-0.015543</td>\n",
+       "      <td>0.031404</td>\n",
+       "      <td>-0.017942</td>\n",
+       "      <td>-0.003518</td>\n",
+       "      <td>0.007626</td>\n",
+       "      <td>0.020056</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>247_x</th>\n",
+       "      <td>0.024251</td>\n",
+       "      <td>-0.001501</td>\n",
+       "      <td>0.014759</td>\n",
+       "      <td>0.004610</td>\n",
+       "      <td>-0.006585</td>\n",
+       "      <td>-0.013413</td>\n",
+       "      <td>0.040374</td>\n",
+       "      <td>0.000685</td>\n",
+       "      <td>0.022424</td>\n",
+       "      <td>-0.022499</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.006246</td>\n",
+       "      <td>-0.006019</td>\n",
+       "      <td>-0.006536</td>\n",
+       "      <td>-0.011786</td>\n",
+       "      <td>0.039422</td>\n",
+       "      <td>0.002260</td>\n",
+       "      <td>-0.007331</td>\n",
+       "      <td>-0.001406</td>\n",
+       "      <td>-0.002716</td>\n",
+       "      <td>-0.013242</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3_x</th>\n",
+       "      <td>-0.006860</td>\n",
+       "      <td>-0.017289</td>\n",
+       "      <td>-0.009471</td>\n",
+       "      <td>0.015597</td>\n",
+       "      <td>-0.009979</td>\n",
+       "      <td>0.006725</td>\n",
+       "      <td>-0.021784</td>\n",
+       "      <td>-0.020575</td>\n",
+       "      <td>-0.038415</td>\n",
+       "      <td>-0.011056</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.002718</td>\n",
+       "      <td>0.014274</td>\n",
+       "      <td>0.017862</td>\n",
+       "      <td>0.014215</td>\n",
+       "      <td>0.062032</td>\n",
+       "      <td>0.021786</td>\n",
+       "      <td>-0.003386</td>\n",
+       "      <td>-0.008107</td>\n",
+       "      <td>-0.000574</td>\n",
+       "      <td>-0.012473</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>215_y</th>\n",
+       "      <td>0.018804</td>\n",
+       "      <td>0.006761</td>\n",
+       "      <td>-0.004917</td>\n",
+       "      <td>-0.001727</td>\n",
+       "      <td>-0.001286</td>\n",
+       "      <td>0.004768</td>\n",
+       "      <td>0.090750</td>\n",
+       "      <td>-0.026557</td>\n",
+       "      <td>-0.056897</td>\n",
+       "      <td>0.071934</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.001923</td>\n",
+       "      <td>-0.018259</td>\n",
+       "      <td>0.017321</td>\n",
+       "      <td>0.010741</td>\n",
+       "      <td>0.044739</td>\n",
+       "      <td>-0.001906</td>\n",
+       "      <td>0.003171</td>\n",
+       "      <td>0.012691</td>\n",
+       "      <td>0.021180</td>\n",
+       "      <td>-0.001125</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39_y</th>\n",
+       "      <td>0.007506</td>\n",
+       "      <td>0.003677</td>\n",
+       "      <td>-0.005078</td>\n",
+       "      <td>-0.000712</td>\n",
+       "      <td>-0.010931</td>\n",
+       "      <td>0.011326</td>\n",
+       "      <td>-0.016780</td>\n",
+       "      <td>0.009883</td>\n",
+       "      <td>-0.020095</td>\n",
+       "      <td>0.029188</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.008140</td>\n",
+       "      <td>0.005325</td>\n",
+       "      <td>0.005893</td>\n",
+       "      <td>0.006924</td>\n",
+       "      <td>0.046151</td>\n",
+       "      <td>0.004848</td>\n",
+       "      <td>-0.008972</td>\n",
+       "      <td>-0.013802</td>\n",
+       "      <td>0.041432</td>\n",
+       "      <td>-0.007292</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>151_y</th>\n",
+       "      <td>0.000114</td>\n",
+       "      <td>0.007296</td>\n",
+       "      <td>-0.006385</td>\n",
+       "      <td>-0.000763</td>\n",
+       "      <td>-0.007485</td>\n",
+       "      <td>0.008225</td>\n",
+       "      <td>0.082326</td>\n",
+       "      <td>0.034954</td>\n",
+       "      <td>0.135517</td>\n",
+       "      <td>0.145262</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.003022</td>\n",
+       "      <td>0.022633</td>\n",
+       "      <td>0.011221</td>\n",
+       "      <td>0.019455</td>\n",
+       "      <td>0.096007</td>\n",
+       "      <td>0.016421</td>\n",
+       "      <td>-0.006210</td>\n",
+       "      <td>-0.001917</td>\n",
+       "      <td>0.026495</td>\n",
+       "      <td>-0.006740</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>225_x</th>\n",
+       "      <td>0.008989</td>\n",
+       "      <td>0.015538</td>\n",
+       "      <td>-0.007535</td>\n",
+       "      <td>0.001987</td>\n",
+       "      <td>-0.006479</td>\n",
+       "      <td>0.012505</td>\n",
+       "      <td>-0.004841</td>\n",
+       "      <td>0.036215</td>\n",
+       "      <td>0.031599</td>\n",
+       "      <td>-0.019043</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.001395</td>\n",
+       "      <td>-0.003572</td>\n",
+       "      <td>0.012202</td>\n",
+       "      <td>0.009836</td>\n",
+       "      <td>-0.024249</td>\n",
+       "      <td>-0.005761</td>\n",
+       "      <td>-0.005415</td>\n",
+       "      <td>-0.004879</td>\n",
+       "      <td>0.030008</td>\n",
+       "      <td>-0.010826</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>85_y</th>\n",
+       "      <td>-0.013778</td>\n",
+       "      <td>-0.013545</td>\n",
+       "      <td>0.018172</td>\n",
+       "      <td>-0.000293</td>\n",
+       "      <td>0.002305</td>\n",
+       "      <td>-0.014859</td>\n",
+       "      <td>0.019666</td>\n",
+       "      <td>0.016359</td>\n",
+       "      <td>0.051634</td>\n",
+       "      <td>-0.022551</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.007419</td>\n",
+       "      <td>0.008921</td>\n",
+       "      <td>0.000093</td>\n",
+       "      <td>-0.004833</td>\n",
+       "      <td>-0.001465</td>\n",
+       "      <td>-0.000690</td>\n",
+       "      <td>0.002174</td>\n",
+       "      <td>-0.010128</td>\n",
+       "      <td>-0.061124</td>\n",
+       "      <td>0.008596</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>199_x</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-0.006419</td>\n",
+       "      <td>-0.001085</td>\n",
+       "      <td>-0.012671</td>\n",
+       "      <td>0.008373</td>\n",
+       "      <td>0.007883</td>\n",
+       "      <td>-0.019432</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.003016</td>\n",
+       "      <td>-0.015484</td>\n",
+       "      <td>-0.023460</td>\n",
+       "      <td>0.007944</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-0.006941</td>\n",
+       "      <td>0.001313</td>\n",
+       "      <td>-0.002521</td>\n",
+       "      <td>-0.029777</td>\n",
+       "      <td>0.000372</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>208 rows × 730299 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         0         1         2         3         4         5         6       \\\n",
+       "253_x -0.006434 -0.005135  0.003936  0.001123 -0.002732 -0.001861 -0.021329   \n",
+       "125_y  0.000716  0.002270  0.005394 -0.013332  0.003166  0.000206 -0.035705   \n",
+       "247_x  0.024251 -0.001501  0.014759  0.004610 -0.006585 -0.013413  0.040374   \n",
+       "3_x   -0.006860 -0.017289 -0.009471  0.015597 -0.009979  0.006725 -0.021784   \n",
+       "215_y  0.018804  0.006761 -0.004917 -0.001727 -0.001286  0.004768  0.090750   \n",
+       "...         ...       ...       ...       ...       ...       ...       ...   \n",
+       "39_y   0.007506  0.003677 -0.005078 -0.000712 -0.010931  0.011326 -0.016780   \n",
+       "151_y  0.000114  0.007296 -0.006385 -0.000763 -0.007485  0.008225  0.082326   \n",
+       "225_x  0.008989  0.015538 -0.007535  0.001987 -0.006479  0.012505 -0.004841   \n",
+       "85_y  -0.013778 -0.013545  0.018172 -0.000293  0.002305 -0.014859  0.019666   \n",
+       "199_x       NaN -0.006419 -0.001085 -0.012671  0.008373  0.007883 -0.019432   \n",
+       "\n",
+       "         7         8         9       ...    730289    730290    730291  \\\n",
+       "253_x -0.037894 -0.005184 -0.033538  ...  0.000557 -0.007762 -0.012392   \n",
+       "125_y -0.016508 -0.048848 -0.049963  ...  0.003380 -0.021147 -0.012083   \n",
+       "247_x  0.000685  0.022424 -0.022499  ... -0.006246 -0.006019 -0.006536   \n",
+       "3_x   -0.020575 -0.038415 -0.011056  ... -0.002718  0.014274  0.017862   \n",
+       "215_y -0.026557 -0.056897  0.071934  ...  0.001923 -0.018259  0.017321   \n",
+       "...         ...       ...       ...  ...       ...       ...       ...   \n",
+       "39_y   0.009883 -0.020095  0.029188  ... -0.008140  0.005325  0.005893   \n",
+       "151_y  0.034954  0.135517  0.145262  ... -0.003022  0.022633  0.011221   \n",
+       "225_x  0.036215  0.031599 -0.019043  ... -0.001395 -0.003572  0.012202   \n",
+       "85_y   0.016359  0.051634 -0.022551  ...  0.007419  0.008921  0.000093   \n",
+       "199_x       NaN       NaN       NaN  ... -0.003016 -0.015484 -0.023460   \n",
+       "\n",
+       "         730292    730293    730294    730295    730296    730297    730298  \n",
+       "253_x  0.002060 -0.003150 -0.002462 -0.006094  0.000048  0.012364  0.002390  \n",
+       "125_y -0.015543  0.031404 -0.017942 -0.003518  0.007626  0.020056       NaN  \n",
+       "247_x -0.011786  0.039422  0.002260 -0.007331 -0.001406 -0.002716 -0.013242  \n",
+       "3_x    0.014215  0.062032  0.021786 -0.003386 -0.008107 -0.000574 -0.012473  \n",
+       "215_y  0.010741  0.044739 -0.001906  0.003171  0.012691  0.021180 -0.001125  \n",
+       "...         ...       ...       ...       ...       ...       ...       ...  \n",
+       "39_y   0.006924  0.046151  0.004848 -0.008972 -0.013802  0.041432 -0.007292  \n",
+       "151_y  0.019455  0.096007  0.016421 -0.006210 -0.001917  0.026495 -0.006740  \n",
+       "225_x  0.009836 -0.024249 -0.005761 -0.005415 -0.004879  0.030008 -0.010826  \n",
+       "85_y  -0.004833 -0.001465 -0.000690  0.002174 -0.010128 -0.061124  0.008596  \n",
+       "199_x  0.007944       NaN -0.006941  0.001313 -0.002521 -0.029777  0.000372  \n",
+       "\n",
+       "[208 rows x 730299 columns]"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_tumor=no_outlier(train_tumor)\n",
+    "train_tumor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0         0.001698\n",
+       "1        -0.001098\n",
+       "2         0.001686\n",
+       "3         0.000580\n",
+       "4        -0.000642\n",
+       "            ...   \n",
+       "730294   -0.000839\n",
+       "730295   -0.000743\n",
+       "730296   -0.000037\n",
+       "730297    0.001886\n",
+       "730298   -0.000306\n",
+       "Length: 730299, dtype: float64"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_tumor_mean = train_tumor.mean(skipna=True, axis = 0)\n",
+    "train_tumor_mean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>dbeta</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg07881041</td>\n",
+       "      <td>0.001698</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg03513874</td>\n",
+       "      <td>-0.001098</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg05451842</td>\n",
+       "      <td>0.001686</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg14797042</td>\n",
+       "      <td>0.000580</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg09838562</td>\n",
+       "      <td>-0.000642</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730294</th>\n",
+       "      <td>cg19812938</td>\n",
+       "      <td>-0.000839</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730295</th>\n",
+       "      <td>cg06272054</td>\n",
+       "      <td>-0.000743</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730296</th>\n",
+       "      <td>cg07255356</td>\n",
+       "      <td>-0.000037</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730297</th>\n",
+       "      <td>cg24220897</td>\n",
+       "      <td>0.001886</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730298</th>\n",
+       "      <td>cg12325588</td>\n",
+       "      <td>-0.000306</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>730299 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unnamed: 0     dbeta\n",
+       "0       cg07881041  0.001698\n",
+       "1       cg03513874 -0.001098\n",
+       "2       cg05451842  0.001686\n",
+       "3       cg14797042  0.000580\n",
+       "4       cg09838562 -0.000642\n",
+       "...            ...       ...\n",
+       "730294  cg19812938 -0.000839\n",
+       "730295  cg06272054 -0.000743\n",
+       "730296  cg07255356 -0.000037\n",
+       "730297  cg24220897  0.001886\n",
+       "730298  cg12325588 -0.000306\n",
+       "\n",
+       "[730299 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Δβ = pd.merge(df_beta.iloc[:,:1], pd.DataFrame(train_tumor_mean, columns = [\"dbeta\"]), left_index=True, right_index=True)\n",
+    "Δβ"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
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+       "\n",
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>gene_x</th>\n",
+       "      <th>feature_x</th>\n",
+       "      <th>gene_y</th>\n",
+       "      <th>feature_y</th>\n",
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+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg07677157</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>IGR</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>IGR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg01485645</td>\n",
+       "      <td>MLLT6</td>\n",
+       "      <td>Body</td>\n",
+       "      <td>MLLT6</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg15261712</td>\n",
+       "      <td>CDK6</td>\n",
+       "      <td>3'UTR</td>\n",
+       "      <td>CDK6</td>\n",
+       "      <td>3'UTR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg08173263</td>\n",
+       "      <td>LPHN1</td>\n",
+       "      <td>Body</td>\n",
+       "      <td>LPHN1</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg22652406</td>\n",
+       "      <td>DNAJC4</td>\n",
+       "      <td>TSS200</td>\n",
+       "      <td>DNAJC4</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>212521</th>\n",
+       "      <td>cg06961284</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>TUBGCP3</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>212522</th>\n",
+       "      <td>cg00895836</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>IGR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>212523</th>\n",
+       "      <td>cg25296374</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>IGR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>212524</th>\n",
+       "      <td>cg18254983</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>KLK15</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>212525</th>\n",
+       "      <td>cg03266453</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>EN1</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>212526 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unnamed: 0  gene_x feature_x   gene_y feature_y\n",
+       "0       cg07677157     NaN       IGR      NaN       IGR\n",
+       "1       cg01485645   MLLT6      Body    MLLT6      Body\n",
+       "2       cg15261712    CDK6     3'UTR     CDK6     3'UTR\n",
+       "3       cg08173263   LPHN1      Body    LPHN1      Body\n",
+       "4       cg22652406  DNAJC4    TSS200   DNAJC4    TSS200\n",
+       "...            ...     ...       ...      ...       ...\n",
+       "212521  cg06961284     NaN       NaN  TUBGCP3      Body\n",
+       "212522  cg00895836     NaN       NaN      NaN       IGR\n",
+       "212523  cg25296374     NaN       NaN      NaN       IGR\n",
+       "212524  cg18254983     NaN       NaN    KLK15      Body\n",
+       "212525  cg03266453     NaN       NaN      EN1   TSS1500\n",
+       "\n",
+       "[212526 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dmp_train_0 = pd.read_csv(f\"source/GSE243529/DMP_result_0.csv\")\n",
+    "dmp_train_1 = pd.read_csv(f\"source/GSE243529/DMP_result_1.csv\")\n",
+    "\n",
+    "dmp_train = pd.merge(left=dmp_train_0,right=dmp_train_1,on=\"Unnamed: 0\",how=\"outer\")\n",
+    "\n",
+    "# 去除重複值，實現UNION效果\n",
+    "\n",
+    "\n",
+    "result = dmp_train.drop_duplicates().reset_index(drop=True)\n",
+    "\n",
+    "(result[[\"Unnamed: 0\",\"gene_y\",\"feature_y\"]])\n",
+    "\n",
+    "result= result[[\"Unnamed: 0\",\"gene_x\",\"feature_x\",\"gene_y\",\"feature_y\"]]\n",
+    "# print(result.head(3))\n",
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>gene</th>\n",
+       "      <th>feature</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg07677157</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>IGR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg01485645</td>\n",
+       "      <td>MLLT6</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg15261712</td>\n",
+       "      <td>CDK6</td>\n",
+       "      <td>3'UTR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg08173263</td>\n",
+       "      <td>LPHN1</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg22652406</td>\n",
+       "      <td>DNAJC4</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>212521</th>\n",
+       "      <td>cg06961284</td>\n",
+       "      <td>TUBGCP3</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>212522</th>\n",
+       "      <td>cg00895836</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>IGR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>212523</th>\n",
+       "      <td>cg25296374</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>IGR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>212524</th>\n",
+       "      <td>cg18254983</td>\n",
+       "      <td>KLK15</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>212525</th>\n",
+       "      <td>cg03266453</td>\n",
+       "      <td>EN1</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>212526 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unnamed: 0     gene  feature\n",
+       "0       cg07677157      NaN      IGR\n",
+       "1       cg01485645    MLLT6     Body\n",
+       "2       cg15261712     CDK6    3'UTR\n",
+       "3       cg08173263    LPHN1     Body\n",
+       "4       cg22652406   DNAJC4   TSS200\n",
+       "...            ...      ...      ...\n",
+       "212521  cg06961284  TUBGCP3     Body\n",
+       "212522  cg00895836      NaN      IGR\n",
+       "212523  cg25296374      NaN      IGR\n",
+       "212524  cg18254983    KLK15     Body\n",
+       "212525  cg03266453      EN1  TSS1500\n",
+       "\n",
+       "[212526 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "result_tmp = result\n",
+    "\n",
+    "result_tmp['gene'] = result_tmp['gene_x'].combine_first(result_tmp['gene_y'])\n",
+    "result_tmp['feature'] = result_tmp['feature_x'].combine_first(result_tmp['feature_y'])\n",
+    "\n",
+    "# 移除多餘的欄位，只保留合併後的資料\n",
+    "result_tmp = result_tmp[['Unnamed: 0', 'gene', 'feature']]\n",
+    "\n",
+    "dmp_train = result_tmp\n",
+    "dmp_train\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "raw train shape: (212526, 3)\n",
+      "after dropna: (163189, 3)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# dmp_train = pd.read_csv(f\"../champ_result/DMP_result_{file_endings}.csv\")\n",
+    "\n",
+    "\n",
+    "print(f\"raw train shape: {dmp_train.shape}\")\n",
+    "dmp_train = dmp_train[[\"Unnamed: 0\", \"gene\",\"feature\"]]\n",
+    "dmp_train.dropna(inplace=True)\n",
+    "print(f\"after dropna: {dmp_train.shape}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>dbeta</th>\n",
+       "      <th>gene</th>\n",
+       "      <th>feature</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg05451842</td>\n",
+       "      <td>0.001686</td>\n",
+       "      <td>ITPK1</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg23875663</td>\n",
+       "      <td>-0.011174</td>\n",
+       "      <td>PCSK2</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg12406992</td>\n",
+       "      <td>-0.004469</td>\n",
+       "      <td>MEX3A</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg05493344</td>\n",
+       "      <td>-0.009112</td>\n",
+       "      <td>SARDH</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg10136773</td>\n",
+       "      <td>-0.000650</td>\n",
+       "      <td>SESN3</td>\n",
+       "      <td>3'UTR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>161998</th>\n",
+       "      <td>cg11236429</td>\n",
+       "      <td>0.001712</td>\n",
+       "      <td>NBLA00301</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>161999</th>\n",
+       "      <td>cg03641640</td>\n",
+       "      <td>-0.008229</td>\n",
+       "      <td>RASA3</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>162000</th>\n",
+       "      <td>cg16115720</td>\n",
+       "      <td>0.001475</td>\n",
+       "      <td>CD34</td>\n",
+       "      <td>1stExon</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>162001</th>\n",
+       "      <td>cg26660754</td>\n",
+       "      <td>-0.000271</td>\n",
+       "      <td>APC</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>162002</th>\n",
+       "      <td>cg23020486</td>\n",
+       "      <td>-0.000175</td>\n",
+       "      <td>EDARADD</td>\n",
+       "      <td>5'UTR</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>162003 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unnamed: 0     dbeta       gene  feature\n",
+       "0       cg05451842  0.001686      ITPK1     Body\n",
+       "1       cg23875663 -0.011174      PCSK2     Body\n",
+       "2       cg12406992 -0.004469      MEX3A     Body\n",
+       "3       cg05493344 -0.009112      SARDH     Body\n",
+       "4       cg10136773 -0.000650      SESN3    3'UTR\n",
+       "...            ...       ...        ...      ...\n",
+       "161998  cg11236429  0.001712  NBLA00301     Body\n",
+       "161999  cg03641640 -0.008229      RASA3     Body\n",
+       "162000  cg16115720  0.001475       CD34  1stExon\n",
+       "162001  cg26660754 -0.000271        APC   TSS200\n",
+       "162002  cg23020486 -0.000175    EDARADD    5'UTR\n",
+       "\n",
+       "[162003 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result = pd.merge(Δβ, dmp_train, on=\"Unnamed: 0\", how=\"inner\")\n",
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def find_max_dBeta_grouped(group):\n",
+    "    idx_max = group['dbeta'].abs().idxmax()\n",
+    "    return group.loc[idx_max]\n",
+    "\n",
+    "result_max_per_gene = result.groupby(\"gene\").apply(find_max_dBeta_grouped).reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "single = pd.read_csv('external_result/matchgene174_single_3Y10__OR2.txt', sep='\\t', header=None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>dbeta</th>\n",
+       "      <th>gene</th>\n",
+       "      <th>feature</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg10222734</td>\n",
+       "      <td>-0.010651</td>\n",
+       "      <td>A1CF</td>\n",
+       "      <td>5'UTR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg11139127</td>\n",
+       "      <td>-0.009722</td>\n",
+       "      <td>A2M</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>cg23546356</td>\n",
+       "      <td>-0.016178</td>\n",
+       "      <td>A2ML1</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>cg13001012</td>\n",
+       "      <td>-0.008898</td>\n",
+       "      <td>AADAC</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>cg00309402</td>\n",
+       "      <td>-0.022852</td>\n",
+       "      <td>AADAT</td>\n",
+       "      <td>3'UTR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18435</th>\n",
+       "      <td>cg21317279</td>\n",
+       "      <td>0.009295</td>\n",
+       "      <td>ZNRD1</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18438</th>\n",
+       "      <td>cg21918728</td>\n",
+       "      <td>-0.008992</td>\n",
+       "      <td>ZNRF3</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18455</th>\n",
+       "      <td>cg10659886</td>\n",
+       "      <td>0.027345</td>\n",
+       "      <td>ZSCAN18</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18475</th>\n",
+       "      <td>cg02286335</td>\n",
+       "      <td>0.007187</td>\n",
+       "      <td>ZWINT</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18479</th>\n",
+       "      <td>cg03100196</td>\n",
+       "      <td>0.003925</td>\n",
+       "      <td>ZYX</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7904 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Unnamed: 0     dbeta     gene  feature\n",
+       "1      cg10222734 -0.010651     A1CF    5'UTR\n",
+       "4      cg11139127 -0.009722      A2M     Body\n",
+       "5      cg23546356 -0.016178    A2ML1  TSS1500\n",
+       "12     cg13001012 -0.008898    AADAC  TSS1500\n",
+       "16     cg00309402 -0.022852    AADAT    3'UTR\n",
+       "...           ...       ...      ...      ...\n",
+       "18435  cg21317279  0.009295    ZNRD1     Body\n",
+       "18438  cg21918728 -0.008992    ZNRF3     Body\n",
+       "18455  cg10659886  0.027345  ZSCAN18     Body\n",
+       "18475  cg02286335  0.007187    ZWINT   TSS200\n",
+       "18479  cg03100196  0.003925      ZYX  TSS1500\n",
+       "\n",
+       "[7904 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result_max_per_gene_single = result_max_per_gene[result_max_per_gene['gene'].isin(single[0])]\n",
+    "result_max_per_gene_single"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result_max_per_gene_single.to_csv(f\"result/aba_GSE243529/dbeta.csv\", index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>dbeta</th>\n",
+       "      <th>gene</th>\n",
+       "      <th>feature</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg10222734</td>\n",
+       "      <td>-0.010651</td>\n",
+       "      <td>A1CF</td>\n",
+       "      <td>5'UTR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg11139127</td>\n",
+       "      <td>-0.009722</td>\n",
+       "      <td>A2M</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>cg23546356</td>\n",
+       "      <td>-0.016178</td>\n",
+       "      <td>A2ML1</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>cg13001012</td>\n",
+       "      <td>-0.008898</td>\n",
+       "      <td>AADAC</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>cg00309402</td>\n",
+       "      <td>-0.022852</td>\n",
+       "      <td>AADAT</td>\n",
+       "      <td>3'UTR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18435</th>\n",
+       "      <td>cg21317279</td>\n",
+       "      <td>0.009295</td>\n",
+       "      <td>ZNRD1</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18438</th>\n",
+       "      <td>cg21918728</td>\n",
+       "      <td>-0.008992</td>\n",
+       "      <td>ZNRF3</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18455</th>\n",
+       "      <td>cg10659886</td>\n",
+       "      <td>0.027345</td>\n",
+       "      <td>ZSCAN18</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18475</th>\n",
+       "      <td>cg02286335</td>\n",
+       "      <td>0.007187</td>\n",
+       "      <td>ZWINT</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18479</th>\n",
+       "      <td>cg03100196</td>\n",
+       "      <td>0.003925</td>\n",
+       "      <td>ZYX</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7904 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Unnamed: 0     dbeta     gene  feature\n",
+       "1      cg10222734 -0.010651     A1CF    5'UTR\n",
+       "4      cg11139127 -0.009722      A2M     Body\n",
+       "5      cg23546356 -0.016178    A2ML1  TSS1500\n",
+       "12     cg13001012 -0.008898    AADAC  TSS1500\n",
+       "16     cg00309402 -0.022852    AADAT    3'UTR\n",
+       "...           ...       ...      ...      ...\n",
+       "18435  cg21317279  0.009295    ZNRD1     Body\n",
+       "18438  cg21918728 -0.008992    ZNRF3     Body\n",
+       "18455  cg10659886  0.027345  ZSCAN18     Body\n",
+       "18475  cg02286335  0.007187    ZWINT   TSS200\n",
+       "18479  cg03100196  0.003925      ZYX  TSS1500\n",
+       "\n",
+       "[7904 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result_max_per_gene_single"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(592, 4)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>dbeta</th>\n",
+       "      <th>gene</th>\n",
+       "      <th>feature</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>cg10118456</td>\n",
+       "      <td>0.028641</td>\n",
+       "      <td>ABCC1</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>84</th>\n",
+       "      <td>cg13460556</td>\n",
+       "      <td>0.024486</td>\n",
+       "      <td>ABHD2</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>93</th>\n",
+       "      <td>cg15626105</td>\n",
+       "      <td>-0.026561</td>\n",
+       "      <td>ABI3BP</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>99</th>\n",
+       "      <td>cg12020464</td>\n",
+       "      <td>0.027008</td>\n",
+       "      <td>ABO</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>108</th>\n",
+       "      <td>cg07660627</td>\n",
+       "      <td>0.035745</td>\n",
+       "      <td>ACACA</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18133</th>\n",
+       "      <td>cg01672042</td>\n",
+       "      <td>0.041204</td>\n",
+       "      <td>ZNF423</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18205</th>\n",
+       "      <td>cg14269096</td>\n",
+       "      <td>-0.032189</td>\n",
+       "      <td>ZNF532</td>\n",
+       "      <td>5'UTR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18315</th>\n",
+       "      <td>cg20671910</td>\n",
+       "      <td>0.025048</td>\n",
+       "      <td>ZNF687</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18317</th>\n",
+       "      <td>cg07000116</td>\n",
+       "      <td>0.023883</td>\n",
+       "      <td>ZNF689</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18455</th>\n",
+       "      <td>cg10659886</td>\n",
+       "      <td>0.027345</td>\n",
+       "      <td>ZSCAN18</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>592 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Unnamed: 0     dbeta     gene feature\n",
+       "51     cg10118456  0.028641    ABCC1    Body\n",
+       "84     cg13460556  0.024486    ABHD2    Body\n",
+       "93     cg15626105 -0.026561   ABI3BP    Body\n",
+       "99     cg12020464  0.027008      ABO    Body\n",
+       "108    cg07660627  0.035745    ACACA    Body\n",
+       "...           ...       ...      ...     ...\n",
+       "18133  cg01672042  0.041204   ZNF423    Body\n",
+       "18205  cg14269096 -0.032189   ZNF532   5'UTR\n",
+       "18315  cg20671910  0.025048   ZNF687    Body\n",
+       "18317  cg07000116  0.023883   ZNF689    Body\n",
+       "18455  cg10659886  0.027345  ZSCAN18    Body\n",
+       "\n",
+       "[592 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "check = result_max_per_gene_single.loc[result_max_per_gene_single[\"dbeta\"].abs() > 0.023]\n",
+    "print(check.shape)\n",
+    "check"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "253_x    0.596056\n",
+      "125_y    0.583733\n",
+      "247_x    0.591512\n",
+      "3_x      0.586937\n",
+      "215_y    0.603334\n",
+      "           ...   \n",
+      "39_y     0.594678\n",
+      "151_y    0.610348\n",
+      "225_x    0.593444\n",
+      "85_y     0.593369\n",
+      "199_x    0.568784\n",
+      "Length: 208, dtype: float64\n",
+      "0         0.939303\n",
+      "1         0.951060\n",
+      "2         0.034716\n",
+      "3         0.973576\n",
+      "4         0.019429\n",
+      "            ...   \n",
+      "730294    0.881254\n",
+      "730295    0.015123\n",
+      "730296    0.026083\n",
+      "730297    0.919887\n",
+      "730298    0.019284\n",
+      "Length: 730299, dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "liquid_tumor_avg = k.mean(skipna=True, axis = 0)\n",
+    "\n",
+    "freq, bins = np.histogram(liquid_tumor_avg, bins=100, range=(0, 1))\n",
+    "\n",
+    "plt.plot(bins[:-1], freq, linestyle='-')\n",
+    "plt.xlabel('liquid_tumor_avg')\n",
+    "plt.ylabel('Frequency')\n",
+    "plt.title('liquid_tumor_avg')\n",
+    "plt.show()\n",
+    "\n",
+    "print(k.mean(skipna=True, axis = 1))\n",
+    "print(k.mean(skipna=True, axis = 0))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "461_x    0.594288\n",
+      "487_y    0.595312\n",
+      "325_x    0.592389\n",
+      "333_x    0.597179\n",
+      "417_x    0.591353\n",
+      "           ...   \n",
+      "353_x    0.594432\n",
+      "463_y    0.599920\n",
+      "373_x    0.587521\n",
+      "403_y    0.598754\n",
+      "331_x    0.591103\n",
+      "Length: 210, dtype: float64\n",
+      "0         0.938926\n",
+      "1         0.952476\n",
+      "2         0.032351\n",
+      "3         0.974024\n",
+      "4         0.018999\n",
+      "            ...   \n",
+      "730294    0.881875\n",
+      "730295    0.014691\n",
+      "730296    0.025056\n",
+      "730297    0.921886\n",
+      "730298    0.018928\n",
+      "Length: 730299, dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "liquid_normal_avg = kk.mean(skipna=True, axis = 0)\n",
+    "\n",
+    "freq, bins = np.histogram(liquid_normal_avg, bins=100, range=(0, 1))\n",
+    "\n",
+    "plt.plot(bins[:-1], freq, linestyle='-')\n",
+    "plt.xlabel('liquid_normal_avg')\n",
+    "plt.ylabel('Frequency')\n",
+    "plt.title('liquid_normal_avg')\n",
+    "plt.show()\n",
+    "print(kk.mean(skipna=True, axis = 1))\n",
+    "print(kk.mean(skipna=True, axis = 0))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Tumor average per feature: 253_x    0.596056\n",
+      "125_y    0.583733\n",
+      "247_x    0.591512\n",
+      "3_x      0.586937\n",
+      "215_y    0.603334\n",
+      "           ...   \n",
+      "39_y     0.594678\n",
+      "151_y    0.610348\n",
+      "225_x    0.593444\n",
+      "85_y     0.593369\n",
+      "199_x    0.568784\n",
+      "Length: 208, dtype: float64\n",
+      "Tumor average across samples: 0         0.939303\n",
+      "1         0.951060\n",
+      "2         0.034716\n",
+      "3         0.973576\n",
+      "4         0.019429\n",
+      "            ...   \n",
+      "730294    0.881254\n",
+      "730295    0.015123\n",
+      "730296    0.026083\n",
+      "730297    0.919887\n",
+      "730298    0.019284\n",
+      "Length: 730299, dtype: float64\n",
+      "Normal average per feature: 461_x    0.594288\n",
+      "487_y    0.595312\n",
+      "325_x    0.592389\n",
+      "333_x    0.597179\n",
+      "417_x    0.591353\n",
+      "           ...   \n",
+      "353_x    0.594432\n",
+      "463_y    0.599920\n",
+      "373_x    0.587521\n",
+      "403_y    0.598754\n",
+      "331_x    0.591103\n",
+      "Length: 210, dtype: float64\n",
+      "Normal average across samples: 0         0.938926\n",
+      "1         0.952476\n",
+      "2         0.032351\n",
+      "3         0.974024\n",
+      "4         0.018999\n",
+      "            ...   \n",
+      "730294    0.881875\n",
+      "730295    0.014691\n",
+      "730296    0.025056\n",
+      "730297    0.921886\n",
+      "730298    0.018928\n",
+      "Length: 730299, dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# 计算 tumor 的平均值\n",
+    "liquid_tumor_avg = k.mean(skipna=True, axis=0)\n",
+    "\n",
+    "# 计算 normal 的平均值\n",
+    "liquid_normal_avg = kk.mean(skipna=True, axis=0)\n",
+    "\n",
+    "# 计算 histogram\n",
+    "freq_tumor, bins_tumor = np.histogram(liquid_tumor_avg, bins=100, range=(0, 1))\n",
+    "freq_normal, bins_normal = np.histogram(liquid_normal_avg, bins=100, range=(0, 1))\n",
+    "\n",
+    "# 绘制 histogram\n",
+    "\n",
+    "plt.plot(bins_normal[:-1], freq_normal, linestyle='-', label='Normal', color='b')\n",
+    "plt.plot(bins_tumor[:-1], freq_tumor, linestyle='-', label='Tumor', color='r')\n",
+    "\n",
+    "# 设置标签和标题\n",
+    "plt.xlabel('Average Value')\n",
+    "plt.ylabel('Frequency')\n",
+    "plt.title('Tumor vs Normal Average Value')\n",
+    "plt.legend()\n",
+    "\n",
+    "# 显示图表\n",
+    "plt.show()\n",
+    "\n",
+    "# 打印平均值\n",
+    "print(\"Tumor average per feature:\", k.mean(skipna=True, axis=1))\n",
+    "print(\"Tumor average across samples:\", k.mean(skipna=True, axis=0))\n",
+    "print(\"Normal average per feature:\", kk.mean(skipna=True, axis=1))\n",
+    "print(\"Normal average across samples:\", kk.mean(skipna=True, axis=0))\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/process/ics_aba/filter_TSS_hyper_GSE243529.ipynb b/process/ics_aba/filter_TSS_hyper_GSE243529.ipynb
new file mode 100644
index 0000000..e359083
--- /dev/null
+++ b/process/ics_aba/filter_TSS_hyper_GSE243529.ipynb
@@ -0,0 +1,261 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>dbeta</th>\n",
+       "      <th>gene</th>\n",
+       "      <th>feature</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>cg10222734</td>\n",
+       "      <td>-0.010651</td>\n",
+       "      <td>A1CF</td>\n",
+       "      <td>5'UTR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>cg11139127</td>\n",
+       "      <td>-0.009722</td>\n",
+       "      <td>A2M</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>cg23546356</td>\n",
+       "      <td>-0.016178</td>\n",
+       "      <td>A2ML1</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>cg13001012</td>\n",
+       "      <td>-0.008898</td>\n",
+       "      <td>AADAC</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>cg00309402</td>\n",
+       "      <td>-0.022852</td>\n",
+       "      <td>AADAT</td>\n",
+       "      <td>3'UTR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7899</th>\n",
+       "      <td>cg21317279</td>\n",
+       "      <td>0.009295</td>\n",
+       "      <td>ZNRD1</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7900</th>\n",
+       "      <td>cg21918728</td>\n",
+       "      <td>-0.008992</td>\n",
+       "      <td>ZNRF3</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7901</th>\n",
+       "      <td>cg10659886</td>\n",
+       "      <td>0.027345</td>\n",
+       "      <td>ZSCAN18</td>\n",
+       "      <td>Body</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7902</th>\n",
+       "      <td>cg02286335</td>\n",
+       "      <td>0.007187</td>\n",
+       "      <td>ZWINT</td>\n",
+       "      <td>TSS200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7903</th>\n",
+       "      <td>cg03100196</td>\n",
+       "      <td>0.003925</td>\n",
+       "      <td>ZYX</td>\n",
+       "      <td>TSS1500</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7904 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Unnamed: 0     dbeta     gene  feature\n",
+       "0     cg10222734 -0.010651     A1CF    5'UTR\n",
+       "1     cg11139127 -0.009722      A2M     Body\n",
+       "2     cg23546356 -0.016178    A2ML1  TSS1500\n",
+       "3     cg13001012 -0.008898    AADAC  TSS1500\n",
+       "4     cg00309402 -0.022852    AADAT    3'UTR\n",
+       "...          ...       ...      ...      ...\n",
+       "7899  cg21317279  0.009295    ZNRD1     Body\n",
+       "7900  cg21918728 -0.008992    ZNRF3     Body\n",
+       "7901  cg10659886  0.027345  ZSCAN18     Body\n",
+       "7902  cg02286335  0.007187    ZWINT   TSS200\n",
+       "7903  cg03100196  0.003925      ZYX  TSS1500\n",
+       "\n",
+       "[7904 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "df_gene_single_dbeta = pd.read_csv(\"result/GSE243529_aba/dbeta.csv\")\n",
+    "df_gene_single_dbeta"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "      Unnamed: 0     dbeta     gene feature\n",
+      "4     cg00309402 -0.022852    AADAT   3'UTR\n",
+      "22    cg10118456  0.028641    ABCC1    Body\n",
+      "35    cg13460556  0.024486    ABHD2    Body\n",
+      "41    cg15626105 -0.026561   ABI3BP    Body\n",
+      "42    cg02915920  0.021758     ABL1    Body\n",
+      "...          ...       ...      ...     ...\n",
+      "7860  cg01672042  0.041204   ZNF423    Body\n",
+      "7872  cg14269096 -0.032189   ZNF532   5'UTR\n",
+      "7886  cg20671910  0.025048   ZNF687    Body\n",
+      "7887  cg07000116  0.023883   ZNF689    Body\n",
+      "7901  cg10659886  0.027345  ZSCAN18    Body\n",
+      "\n",
+      "[987 rows x 4 columns] (987, 4)\n",
+      "      Unnamed: 0     dbeta     gene feature\n",
+      "22    cg10118456  0.028641    ABCC1    Body\n",
+      "35    cg13460556  0.024486    ABHD2    Body\n",
+      "42    cg02915920  0.021758     ABL1    Body\n",
+      "44    cg12020464  0.027008      ABO    Body\n",
+      "46    cg07660627  0.035745    ACACA    Body\n",
+      "...          ...       ...      ...     ...\n",
+      "7825  cg10687936  0.030197   ZNF148   5'UTR\n",
+      "7860  cg01672042  0.041204   ZNF423    Body\n",
+      "7886  cg20671910  0.025048   ZNF687    Body\n",
+      "7887  cg07000116  0.023883   ZNF689    Body\n",
+      "7901  cg10659886  0.027345  ZSCAN18    Body\n",
+      "\n",
+      "[642 rows x 4 columns] (642, 4)\n",
+      "      Unnamed: 0     dbeta     gene  feature\n",
+      "50    cg10523679  0.021226    ACADM  TSS1500\n",
+      "73    cg20707765  0.024253    ACSL5  TSS1500\n",
+      "258   cg19536664  0.030384   ALOX12  TSS1500\n",
+      "298   cg14904662  0.020543     ANK1  TSS1500\n",
+      "395   cg01699630  0.024147     ARG1  TSS1500\n",
+      "...          ...       ...      ...      ...\n",
+      "6782  cg16688533  0.040679     STC1  TSS1500\n",
+      "6843  cg03681335  0.029692  SULT1C2  TSS1500\n",
+      "6853  cg15100599  0.023953    SUSD4  TSS1500\n",
+      "7067  cg02569115  0.028042    TIMP2  TSS1500\n",
+      "7599  cg09276451  0.021343     VASN  TSS1500\n",
+      "\n",
+      "[92 rows x 4 columns] (92, 4)\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_gene_single_dbeta_threshold = df_gene_single_dbeta[abs((df_gene_single_dbeta['dbeta'])) > 0.02]\n",
+    "print(df_gene_single_dbeta_threshold,df_gene_single_dbeta_threshold.shape)\n",
+    "\n",
+    "\n",
+    "df_gene_single_dbeta_threshold_hyper = df_gene_single_dbeta_threshold[df_gene_single_dbeta_threshold['dbeta']>0]\n",
+    "print(df_gene_single_dbeta_threshold_hyper,df_gene_single_dbeta_threshold_hyper.shape)\n",
+    "\n",
+    "\n",
+    "df_gene_single_dbeta_threshold_hyper_TSS = df_gene_single_dbeta_threshold_hyper.loc[(df_gene_single_dbeta_threshold_hyper['feature'] == 'TSS200') | (df_gene_single_dbeta_threshold_hyper['feature'] == 'TSS1500')]\n",
+    "print(df_gene_single_dbeta_threshold_hyper_TSS,df_gene_single_dbeta_threshold_hyper_TSS.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_gene_single_dbeta_threshold_hyper_TSS = df_gene_single_dbeta_threshold_hyper_TSS[[\"Unnamed: 0\",\"dbeta\",\"gene\"]]\n",
+    "df_gene_single_dbeta_threshold_hyper_TSS.to_csv(\"result/GSE243529_aba/dbeta_0.8_abs_0.02_hyper_TSS.csv\",index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "df_gene_single_dbeta_threshold_hyper_TSS['gene'].to_csv(\"result/GSE243529_aba/dbeta_0.8_abs_0.02_hyper_TSS_genelist.csv\",index=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/process/set_dbeta_threshold.ipynb b/process/set_dbeta_threshold.ipynb
index ce07a78..af18a42 100644
--- a/process/set_dbeta_threshold.ipynb
+++ b/process/set_dbeta_threshold.ipynb
@@ -744,7 +744,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.10.7"
   }
  },
  "nbformat": 4,
diff --git a/process/split_dataset.ipynb b/process/split_dataset.ipynb
index c4296b5..dd0c896 100644
--- a/process/split_dataset.ipynb
+++ b/process/split_dataset.ipynb
@@ -545,7 +545,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.10.7"
   }
  },
  "nbformat": 4,