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  1. 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
    Tue Sep 09 17:54:28 UTC 2025
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  2. RFECV scikit-learn 1.7.2 documentation

    remove at each iteration. If within (0.0, 1.0), then step corresponds...rankings across (k)th fold. Selected (i.e., estimated best) features...
    scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFECV.html
    Tue Sep 09 17:54:29 UTC 2025
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  3. SpectralCoclustering scikit-learn 1.7.2 docum...

    = np . array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7 ],...clustering . row_labels_ array([0, 1, 1, 0, 0, 0], dtype=int32) >>>...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralCoclustering.html
    Tue Sep 09 17:54:29 UTC 2025
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  4. BisectingKMeans scikit-learn 1.7.2 documentation

    np . array ([[ 1 , 1 ], [ 10 , 1 ], [ 3 , 1 ], ... [ 10 , 0 ],...], [ 2 , 1 ], [ 10 , 2 ], ... [ 10 , 8 ], [ 10 , 9 ], [ 10 , 10...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.BisectingKMeans.html
    Tue Sep 09 17:54:31 UTC 2025
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  5. make_classification scikit-learn 1.7.2 docume...

    [np.int64(0), np.int64(0), np.int64(1), np.int64(1), np.int64(0)].... shape (100, 20) >>> y . shape (100,) >>> list ( y [: 5 ]) [np.int64(0),...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_classification.html
    Tue Sep 09 17:54:31 UTC 2025
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  6. 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
    Tue Sep 09 17:54:29 UTC 2025
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  7. 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
    Tue Sep 09 17:54:28 UTC 2025
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  8. RidgeClassifier scikit-learn 1.7.2 documentation

    ‘cholesky, lsqr, sparse_cg, sag, saga, lbfgs}, default=’auto’...n_samples / (n_classes * np.bincount(y)) . solver {auto, svd, ‘cholesky’,...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeClassifier.html
    Tue Sep 09 17:54:29 UTC 2025
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  9. DummyClassifier scikit-learn 1.7.2 documentation

    np . array ([ - 1 , 1 , 1 , 1 ]) >>> y = np . array ([ 0 , 1...1, 1, 1]) >>> dummy_clf . score ( X , y ) 0.75 fit ( X , y , sample_weight...
    scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html
    Tue Sep 09 17:54:28 UTC 2025
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  10. 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
    Tue Sep 09 17:54:31 UTC 2025
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