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  1. ShuffleSplit — scikit-learn 1.8.0 documen...

    2 , 1 , 2 , 1 , 2 ]) >>> rs = ShuffleSplit...Test: index=[5 2] Fold 1: Train: index=[4 0 2 5] Test: index=[1...
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.ShuffleSplit.html
    Mon Mar 09 14:07:54 UTC 2026
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  2. One-class SVM with non-linear kernel (RBF) &#82...

    2 ) X_train = np . r_ [ X + 2 , X - 2 ] # Generate...randn ( 20 , 2 ) X_test = np . r_ [ X + 2 , X - 2 ] # Generate...
    scikit-learn.org/stable/auto_examples/svm/plot_oneclass.html
    Mon Mar 09 14:07:56 UTC 2026
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  3. Reciprocal rank fusion | Reference

    _id: 2 = 1.0/(1+3) + 1.0/(1+2) = 0.5833 _id: 3 = 1.0/(1+2) + 1.0/(1+1)...from=2, size=2 would return documents [ 2 , 3 ] with ranks [3, 4]...
    www.elastic.co/docs/reference/elasticsearch/rest-apis/reciprocal-rank-fusion
    Fri Jan 30 17:46:17 UTC 2026
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  4. 3.4. Metrics and scoring: quantifying the quali...

    = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2...= [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2...
    scikit-learn.org/stable/modules/model_evaluation.html
    Mon Mar 09 14:07:57 UTC 2026
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  5. RegressorChain — scikit-learn 1.8.0 docum...

    2 ], [ 1 , 1 ], [ 2 , 0 ]] >>> chain...predict ( X ) array([[0., 2.], [1., 1.], [2., 0.]]) fit ( X , Y ,...
    scikit-learn.org/stable/modules/generated/sklearn.multioutput.RegressorChain.html
    Mon Mar 09 14:07:54 UTC 2026
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  6. explained_variance_score — scikit-learn 1...

    = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2...= [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.explained_variance_score.html
    Mon Mar 09 14:07:54 UTC 2026
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  7. Probability Calibration curves — scikit-l...

    add_subplot ( gs [: 2 , : 2 ]) calibration_displays = {}...histogram grid_positions = [( 2 , 0 ), ( 2 , 1 ), ( 3 , 0 ), ( 3 ,...
    scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html
    Mon Mar 09 14:07:56 UTC 2026
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  8. PLSSVD — scikit-learn 1.8.0 documentation

    [ 2. , 2. , 2. ], ... [ 2. , 5. , 4. ]]) >>>...([[ 0.1 , - 0.2 ], ... [ 0.9 , 1.1 ], ... [ 6.2 , 5.9 ], ... [...
    scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSSVD.html
    Mon Mar 09 14:07:54 UTC 2026
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  9. top_k_accuracy_score — scikit-learn 1.8.0...

    2 , 0.2 ], # 0 is in top 2 ... [ 0.3 , 0.4 , 0.2 ], # 1...is in top 2 ... [ 0.2 , 0.4 , 0.3 ], # 2 is in top 2 ... [ 0.7...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.top_k_accuracy_score.html
    Mon Mar 09 14:07:54 UTC 2026
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  10. Spectral clustering for image segmentation &#82...

    ]) ** 2 + ( y - center1 [ 1 ]) ** 2 < radius1 ** 2 circle2...]) ** 2 + ( y - center2 [ 1 ]) ** 2 < radius2 ** 2 circle3...
    scikit-learn.org/stable/auto_examples/cluster/plot_segmentation_toy.html
    Mon Mar 09 14:07:56 UTC 2026
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