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  1. CCA — scikit-learn 1.8.0 documentation

    [ 2. , 2. , 2. ], [ 3. , 5. , 4. ]] >>>...y = [[ 0.1 , - 0.2 ], [ 0.9 , 1.1 ], [ 6.2 , 5.9 ], [ 11.9 ,...
    scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.CCA.html
    Mon Mar 23 20:39:21 UTC 2026
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  2. train_test_split — scikit-learn 1.8.0 documenta...

    2 1 4.9 3.0 1.4 0.2 2 4.7 3.2 1.3 0.2 3 4.6 3.1 1.5...1.4 0.2 122 7.7 2.8 6.7 2.0 >>> y_train . head () 96 1 105 2 66...
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html
    Mon Mar 23 20:39:20 UTC 2026
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  3. Feature agglomeration vs. univariate selection ...

    selection # This example compares 2 dimensionality reduction strategies:.... randn ( n_samples , size ** 2 ) for x in X : # smooth data x...
    scikit-learn.org/stable/auto_examples/cluster/plot_feature_agglomeration_vs_univariate_selection....
    Mon Mar 23 20:39:22 UTC 2026
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  4. enet_path — scikit-learn 1.8.0 documentation

    is: ( 1 / ( 2 * n_samples )) * || Y - XW || _Fro ^ 2 + alpha *...mono-output tasks it is: 1 / ( 2 * n_samples ) * || y - Xw ||^...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.enet_path.html
    Mon Mar 23 20:39:23 UTC 2026
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  5. Using KBinsDiscretizer to discretize continuous...

    subplots ( ncols = 2 , sharey = True , figsize = (...predict ( line ), linewidth = 2 , color = "green" , label = "linear...
    scikit-learn.org/stable/auto_examples/preprocessing/plot_discretization.html
    Mon Mar 23 20:39:22 UTC 2026
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  6. incr_mean_variance_axis — scikit-learn 1....

    2 , 2 ]) >>> data = np . array ([ 8 , 1 , 2 , 5...>>> scale = np . array ([ 2 , 3 , 2 ]) >>> csr = sparse...
    scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.incr_mean_variance_axis.html
    Mon Feb 02 09:23:44 UTC 2026
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  7. mean_absolute_error — scikit-learn 1.8.0 docume...

    2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>> mean_absolute_error...]] >>> y_pred = [[ 0 , 2 ], [ - 1 , 2 ], [ 8 , - 5 ]] >>> mean_absolute_error...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html
    Mon Mar 23 20:39:21 UTC 2026
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  8. mean_squared_error — scikit-learn 1.8.0 documen...

    2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>> mean_squared_error...]] >>> y_pred = [[ 0 , 2 ],[ - 1 , 2 ],[ 8 , - 5 ]] >>> mean_squared_error...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html
    Mon Mar 23 20:39:23 UTC 2026
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  9. MultiTaskLasso — scikit-learn 1.8.0 documentation

    2 ], [ 2 , 4 ]], [[ 0 , 0 ], [ 1 , 1 ], [ 2 , 3 ]]) ...Lasso is: ( 1 / ( 2 * n_samples )) * || Y - XW ||^ 2 _Fro + alpha...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLasso.html
    Mon Mar 23 20:39:21 UTC 2026
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  10. PLSRegression — scikit-learn 1.8.0 documentation

    [ 2. , 2. , 2. ], [ 2. , 5. , 4. ]] >>> y =...= [[ 0.1 , - 0.2 ], [ 0.9 , 1.1 ], [ 6.2 , 5.9 ], [ 11.9 , 12.3...
    scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSRegression.html
    Mon Mar 23 20:39:23 UTC 2026
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