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  1. BaggingRegressor scikit-learn 1.7.2 documenta...

    n_estimators = 10 , * , max_samples = 1.0 , max_features = 1.0 , bootstrap...databases and on-line, Machine Learning, 36(1), 85-103, 1999. [ 2 ] L....
    scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingRegressor.html
    Thu Oct 30 14:56:38 UTC 2025
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  2. mean_squared_error scikit-learn 1.7.2 documen...

    1 , 1 ],[ 7 , - 6 ]] >>> y_pred = [[ 0 , 2 ],[ - 1 , 2 ],[ 8...y_pred , multioutput = [ 0.3 , 0.7 ]) 0.825... Gallery examples # Model...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html
    Thu Oct 30 14:56:38 UTC 2025
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  3. hinge_loss scikit-learn 1.7.2 documentation

    array([-2.18, 2.36, 0.09]) >>> hinge_loss ([ - 1 , 1 , 1 ], pred_decision...array ([ 0 , 1 , 2 , 3 ]) >>> labels = np . array ([ 0 , 1 , 2 , 3...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.hinge_loss.html
    Thu Oct 30 14:56:39 UTC 2025
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  4. mean_absolute_error scikit-learn 1.7.2 docume...

    = [ 3 , - 0.5 , 2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>>..., 1 ], [ 7 , - 6 ]] >>> y_pred = [[ 0 , 2 ], [ - 1 , 2 ], [ 8...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html
    Thu Oct 30 14:56:39 UTC 2025
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  5. auc scikit-learn 1.7.2 documentation

    0.1 , 0.4 , 0.35 , 0.8 ]) >>> fpr , tpr , thresholds = metrics...np . array ([ 1 , 1 , 2 , 2 ]) >>> y_score = np . array ([ 0.1...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.auc.html
    Thu Oct 30 14:56:38 UTC 2025
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  6. RandomForestClassifier scikit-learn 1.7.2 doc...

    from 10 to 100 in 0.22. criterion {gini, entropy, log_loss”},...provided. max_features {sqrt, log2, None}, int or float, default=”sqrt”...
    scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html
    Thu Oct 30 14:56:39 UTC 2025
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  7. enet_path scikit-learn 1.7.2 documentation

    true_coef array([ 0. , 0. , 0. , 97.9, 45.7]) >>> alphas , estimated_coef...sklearn.linear_model. enet_path ( X , y , * , l1_ratio = 0.5 , eps = 0.001 , n_alphas...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.enet_path.html
    Thu Oct 30 14:56:38 UTC 2025
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  8. ExtraTreesClassifier scikit-learn 1.7.2 docum...

    from 10 to 100 in 0.22. criterion {gini, entropy, log_loss”},...provided. max_features {sqrt, log2, None}, int or float, default=”sqrt”...
    scikit-learn.org/stable/modules/generated/sklearn.ensemble.ExtraTreesClassifier.html
    Thu Oct 30 14:56:39 UTC 2025
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  9. spectral_clustering scikit-learn 1.7.2 docume...

    array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7 ], [ 3 , 5 ],...array([1, 1, 1, 0, 0, 0]) Gallery examples # Segmenting the picture...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.spectral_clustering.html
    Thu Oct 30 14:56:39 UTC 2025
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  10. ComplementNB scikit-learn 1.7.2 documentation

    size = ( 6 , 100 )) >>> y = np . array ([ 1 , 2 , 3 , 4 , 5 , 6 ])...models. References Rennie, J. D., Shih, L., Teevan, J., & Karger,...
    scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.ComplementNB.html
    Thu Oct 30 14:56:38 UTC 2025
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