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  1. ParameterSampler — scikit-learn 1.6.1 documenta...

    'a' : 1 }, ... { 'b' : 0.923223 , 'a' : 1 }, ... { 'b' : 1.878964...0 ) >>> param_grid = { 'a' :[ 1 , 2 ], 'b' : expon ()} >>> param_list...
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.ParameterSampler.html
    Mon Jan 13 21:12:24 UTC 2025
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  2. Label Propagation digits active learning — scik...

    support 0 1.00 1.00 1.00 22 1 0.85 1.00 0.92 22 2 1.00 1.00 1.00 28...support 0 1.00 1.00 1.00 22 1 0.85 1.00 0.92 22 2 1.00 1.00 1.00 27...
    scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits_active_learni...
    Mon Jan 13 21:12:24 UTC 2025
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  3. binarize — scikit-learn 1.6.1 documentation

    1., 0.], [1., 0., 0.]]) On this page...are replaced by 0, above it by 1. Threshold may not be less than...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.binarize.html
    Fri Jan 10 17:03:55 UTC 2025
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  4. sparse_encode — scikit-learn 1.6.1 documentation

    1 , 0 ], ... [ - 1 , - 1 , 2 ], ... [ 1 , 1 , 1 ], ......>>> X = np . array ([[ - 1 , - 1 , - 1 ], [ 0 , 0 , 3 ]]) >>> dictionary...
    scikit-learn.org/stable/modules/generated/sklearn.decomposition.sparse_encode.html
    Mon Jan 13 21:12:24 UTC 2025
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  5. Decision Tree Regression — scikit-learn 1.6.1 d...

    scatter ( y_1 [:, 0 ], y_1 [:, 1 ], c = "cornflowerblue"...RandomState ( 1 ) X = np . sort ( 5 * rng . rand ( 80 , 1 ), axis =...
    scikit-learn.org/stable/auto_examples/tree/plot_tree_regression.html
    Mon Jan 13 21:12:22 UTC 2025
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  6. Version 0.23 — scikit-learn 1.6.1 documentation

    arguments n_classes < 1 OR length < 1 . #16006 by Rushabh Vasani...Bruno Charron . Version 0.23.1 # May 18 2020 Changelog # sklearn.cluster...
    scikit-learn.org/stable/whats_new/v0.23.html
    Fri Jan 10 17:03:57 UTC 2025
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  7. polynomial_kernel — scikit-learn 1.6.1 document...

    [ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>..., degree = 2 ) array([[1. , 1. ], [1.77..., 2.77...]]) On this...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.polynomial_kernel.html
    Mon Jan 13 21:12:24 UTC 2025
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  8. multilabel_confusion_matrix — scikit-learn 1.6....

    array([[[1, 0], [0, 1]], [[1, 0], [0, 1]], [[0, 1], [1, 0]]]) Multiclass...array([[[3, 1], [0, 2]], [[5, 0], [1, 0]], [[2, 1], [1, 2]]]) On...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.multilabel_confusion_matrix.html
    Mon Jan 13 21:12:24 UTC 2025
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  9. Lagged features for time series forecasting — s...

    1 ± 1.1" "19.9 ± 1.6" "22.7 ± 3.1" "quantile 5"..."39.9 ± 3.2" "17.1 ± 1.1" "19.9 ± 1.6" "22.7 ± 3.1" "quantile 95"...
    scikit-learn.org/stable/auto_examples/applications/plot_time_series_lagged_features.html
    Mon Jan 13 21:12:24 UTC 2025
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  10. OrdinalEncoder — scikit-learn 1.6.1 documentation

    inverse_transform ([[ 1 , 0 ], [ 0 , 1 ]]) array([['Male', 1], ['Female',... =- 1 ) . fit_transform ( X ) array([[ 1., 0.], [ 0., 1.], [...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html
    Fri Jan 10 17:03:55 UTC 2025
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