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  1. MultiOutputRegressor — scikit-learn 1.5.0 docum...

    MultiOutputRegressor ( Ridge ( random_state = 123 )) . fit ( X , y ) >>> regr ....
    scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputRegressor.html
    Fri May 31 14:06:06 UTC 2024
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  2. BaggingRegressor — scikit-learn 1.5.0 documenta...

    123-140, 1996. [ 3 ] T. Ho, “The...
    scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingRegressor.html
    Fri May 31 14:06:04 UTC 2024
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  3. 10. Common pitfalls and recommended practices —...

    >>> rf_123 = RandomForestClassifi ( random_state = 123 ) >>> cross_val_score...cross_val_score ( rf_123 , X , y ) array([0.85, 0.95, 0.95, 0.9...
    scikit-learn.org/stable/common_pitfalls.html
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  4. Plot class probabilities calculated by the Voti...

    random_state = 123 ) clf2 = RandomForestClassifi...n_estimators = 100 , random_state = 123 ) clf3 = GaussianNB () X = np...
    scikit-learn.org/stable/auto_examples/ensemble/plot_voting_probas.html
    Fri May 31 14:06:06 UTC 2024
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  5. Lagged features for time series forecasting — s...

    386905 315 1 164 214 315 247 123 133 33 33 107.875 315 1 71.464286...71.464286 315 1 122 164 214 315 125 123 26 33 109.583333 315 1 72.244048...
    scikit-learn.org/stable/auto_examples/applications/plot_time_series_lagged_features.html
    Fri May 31 14:06:06 UTC 2024
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  6. 1.12. Multiclass and multioutput algorithms — s...

    [ 123.92529176, 21.25719016, -7.84253...
    scikit-learn.org/stable/modules/multiclass.html
    Fri May 31 14:06:04 UTC 2024
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  7. 1.11. Ensembles: Gradient boosting, random fore...

    123-140, 1996. [ H1998 ] T. Ho, “The...
    scikit-learn.org/stable/modules/ensemble.html
    Fri May 31 14:06:06 UTC 2024
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  8. BaggingClassifier — scikit-learn 1.5.0 document...

    123-140, 1996. [ 3 ] T. Ho, “The...
    scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingClassifier.html
    Fri May 31 14:06:06 UTC 2024
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