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  1. Biclustering — scikit-learn 1.7.2 documentation

    Examples concerning biclustering techniques. A demo of the Spectral Biclustering algorithm A demo of the Spectral Co-Clustering algorithm Biclustering documents with the Spectral Co-clustering algo...
    scikit-learn.org/stable/auto_examples/bicluster/index.html
    Wed Sep 24 16:15:26 UTC 2025
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  2. Calibration — scikit-learn 1.7.2 documentation

    Examples illustrating the calibration of predicted probabilities of classifiers. Comparison of Calibration of Classifiers Probability Calibration curves Probability Calibration for 3-class classifi...
    scikit-learn.org/stable/auto_examples/calibration/index.html
    Wed Sep 24 16:15:25 UTC 2025
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  3. Features in Histogram Gradient Boosting Trees —...

    showcasing all points except 2 and 6 in a real life setting...."recorded average" , linewidth = 2 , ax = ax ) for idx , max_iter...
    scikit-learn.org/stable/auto_examples/ensemble/plot_hgbt_regression.html
    Wed Sep 24 16:15:25 UTC 2025
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  4. dump_svmlight_file — scikit-learn 1.7.2 documen...

    Skip to main content Back to top Ctrl + K GitHub Choose version dump_svmlight_file # sklearn.datasets. dump_svmlight_...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.dump_svmlight_file.html
    Wed Sep 24 16:15:24 UTC 2025
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  5. sklearn.discriminant_analysis — scikit-learn 1....

    Linear and quadratic discriminant analysis. User guide. See the Linear and Quadratic Discriminant Analysis section for further details.
    scikit-learn.org/stable/api/sklearn.discriminant_analysis.html
    Wed Sep 24 16:15:25 UTC 2025
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  6. make_column_selector — scikit-learn 1.7.2 docum...

    Gallery examples: Column Transformer with Mixed Types Categorical Feature Support in Gradient Boosting Combine predictors using stacking Evaluation of outlier detection estimators
    scikit-learn.org/stable/modules/generated/sklearn.compose.make_column_selector.html
    Wed Sep 24 16:15:25 UTC 2025
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  7. compute_class_weight — scikit-learn 1.7.2 docum...

    Skip to main content Back to top Ctrl + K GitHub Choose version compute_class_weight # sklearn.utils.class_weight. co...
    scikit-learn.org/stable/modules/generated/sklearn.utils.class_weight.compute_class_weight.html
    Wed Sep 24 16:15:26 UTC 2025
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  8. sklearn.semi_supervised — scikit-learn 1.7.2 do...

    Semi-supervised learning algorithms. These algorithms utilize small amounts of labeled data and large amounts of unlabeled data for classification tasks. User guide. See the Semi-supervised learnin...
    scikit-learn.org/stable/api/sklearn.semi_supervised.html
    Wed Sep 24 16:15:24 UTC 2025
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  9. calinski_harabasz_score — scikit-learn 1.7.2 do...

    Skip to main content Back to top Ctrl + K GitHub Choose version calinski_harabasz_score # sklearn.metrics. calinski_h...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.calinski_harabasz_score.html
    Wed Sep 24 16:15:26 UTC 2025
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  10. get_scorer_names — scikit-learn 1.7.2 documenta...

    Skip to main content Back to top Ctrl + K GitHub Choose version get_scorer_names # sklearn.metrics. get_scorer_names ...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.get_scorer_names.html
    Wed Sep 24 16:15:26 UTC 2025
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