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  1. auto_examples_python.zip

    - l / 2.0) ** 2 + (y - l / 2.0) ** 2 < (l / 2.0) ** 2 mask =...+ 1, figsize=(4 * 2.2, n_classifiers * 2.2), ) evaluation_results...
    scikit-learn.org/stable/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip
    Mon Mar 23 20:39:22 UTC 2026
      1.7M bytes
     
  2. plot_classifier_comparison.zip

    make_classification( n_features=2, n_redundant=0, n_informative=2, random_state=1,...rng = np.random.RandomState(2) X += 2 * rng.uniform(size=X.shape)...
    scikit-learn.org/stable/_downloads/ce35bcc69acbd491cf7ac77fa17889d5/plot_classifier_comparison.zip
    Mon Mar 23 20:39:23 UTC 2026
      10.8K bytes
      1 views
     
  3. VotingClassifier — scikit-learn 1.8.0 documenta...

    2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2 , 2 ]) >>>...- 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2 , 1 ], [ 3...
    scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingClassifier.html
    Mon Mar 23 20:39:20 UTC 2026
      18.6K bytes
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  4. make_friedman2 — scikit-learn 1.8.0 documentation

    0 ] ** 2 + ( X [:, 1 ] * X [:, 2 ] - 1 / ( X [:, 1...[source] # Generate the “Friedman #2” regression problem. This dataset...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman2.html
    Mon Mar 23 20:39:20 UTC 2026
      13.7K bytes
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  5. shuffle — scikit-learn 1.8.0 documentation

    2)> >>> X_sparse . toarray () array([[0., 0.], [2., 1.],...y array([2, 1, 0]) >>> shuffle ( y , n_samples = 2 , random_state...
    scikit-learn.org/stable/modules/generated/sklearn.utils.shuffle.html
    Mon Mar 23 20:39:23 UTC 2026
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  6. LeavePGroupsOut — scikit-learn 1.8.0 documentation

    group=[2] Test: index=[0 2], group=[1 3] Fold 2: Train: index=[0],...array ([ 1 , 2 , 1 ]) >>> groups = np . array ([ 1 , 2 , 3 ]) >>>...
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeavePGroupsOut.html
    Mon Mar 23 20:39:21 UTC 2026
      15.2K bytes
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  7. inplace_row_scale &#8212; scikit-learn 1.8.0 do...

    2 , 5 , 6 ]) &gt;&gt;&gt; scale = np . array ([ 2 , 3 ,...&gt;&gt;&gt; indptr = np . array ([ 0 , 2 , 3 , 4 , 5 ]) &gt;&gt;&gt; indices...
    scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.inplace_row_scale.html
    Mon Feb 02 09:23:44 UTC 2026
      109.1K bytes
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  8. Sparse coding with a precomputed dictionary — s...

    ) ** 2 / width ** 2 ) * np . exp ( - (( x - center ) ** 2 ) /.../ ( 2 * width ** 2 )) ) return x def ricker_matrix ( width , resolution...
    scikit-learn.org/stable/auto_examples/decomposition/plot_sparse_coding.html
    Mon Mar 23 20:39:20 UTC 2026
      17.1K bytes
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  9. pair_confusion_matrix — scikit-learn 1.8.0 docu...

    2 ], [ 0 , 0 , 1 , 1 ]) array([[8, 2], [0, 2]]... Note...confusion matrix \(C\) computes a 2 by 2 similarity matrix between two...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.cluster.pair_confusion_matrix.html
    Mon Mar 23 20:39:20 UTC 2026
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  10. LeaveOneGroupOut — scikit-learn 1.8.0 documenta...

    2 , 1 , 2 ]) >>> groups = np . array ([ 1 , 1 , 2 , 2 ]) >>>...Fold 0: Train: index=[2 3], group=[2 2] Test: index=[0 1], group=[1...
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeaveOneGroupOut.html
    Mon Mar 23 20:39:21 UTC 2026
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