Extend support in DeterministicConstantRegressor to multitargets

[ablaom]

After this PR, one can use DeterministicConstantRegressor with multitargets:

julia> using MLJBase, MLJModels

julia> X, y = make_regression(10, 2; n_targets=3); # synthetic data: two tables

julia> regressor = DeterministicConstantRegressor();

julia> mach = machine(regressor, X, y) |> fit!;
[ Info: Training machine(DeterministicConstantRegressor(), …).

julia> 

julia> fitted_params(mach)
(mean = [-0.08104117873774516 1.5935905587979058 1.0865047090815172],)

julia> 

julia> Xnew, _ = make_regression(3, 2)
(Tables.MatrixTable{Matrix{Float64}} with 3 rows, 2 columns, and schema:
 :x1  Float64
 :x2  Float64, [0.36837556494255974, 0.45959051755066704, 0.23793608647119824])

julia> predict(mach, Xnew)
(Column1 = [-0.08104117873774516, -0.08104117873774516, -0.08104117873774516], Column2 = [1.5935905587979058, 1.5935905587979058, 1.5935905587979058], Column3 = [1.0865047090815172, 1.0865047090815172, 1.0865047090815172])

It also adds tests and a docstring, which this model never had.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 78.68%. Comparing base (7384cde) to head (43c28ec).

Additional details and impacted files

@@            Coverage Diff             @@
##              dev     #602      +/-   ##
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+ Coverage   76.93%   78.68%   +1.74%     
==========================================
  Files           8        8              
  Lines         477      488      +11     
==========================================
+ Hits          367      384      +17     
+ Misses        110      104       -6     

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