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  1. gen_batches — scikit-learn 1.7.2 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version gen_batches # sklearn.utils. gen_batches ( n , batch_...
    scikit-learn.org/stable/modules/generated/sklearn.utils.gen_batches.html
    Thu Oct 09 16:57:45 UTC 2025
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  2. safe_mask — scikit-learn 1.7.2 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version safe_mask # sklearn.utils. safe_mask ( X , mask ) [so...
    scikit-learn.org/stable/modules/generated/sklearn.utils.safe_mask.html
    Thu Oct 09 16:57:48 UTC 2025
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  3. Nearest Centroid Classification — scikit-learn ...

    Sample usage of Nearest Centroid classification. It will plot the decision boundaries for each class.,., Total running time of the script:(0 minutes 0.156 seconds) Launch binder Launch JupyterLite ...
    scikit-learn.org/stable/auto_examples/neighbors/plot_nearest_centroid.html
    Sat Oct 11 07:51:26 UTC 2025
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  4. set_config — scikit-learn 1.7.2 documentation

    Gallery examples: Metadata Routing Displaying Pipelines Introducing the set_output API Post-tuning the decision threshold for cost-sensitive learning Target Encoder’s Internal Cross fitting Release...
    scikit-learn.org/stable/modules/generated/sklearn.set_config.html
    Sat Oct 11 07:51:27 UTC 2025
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  5. sklearn.ensemble — scikit-learn 1.7.2 documenta...

    Ensemble-based methods for classification, regression and anomaly detection. User guide. See the Ensembles: Gradient boosting, random forests, bagging, voting, stacking section for further details.
    scikit-learn.org/stable/api/sklearn.ensemble.html
    Sat Oct 11 07:51:26 UTC 2025
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  6. sklearn.multioutput — scikit-learn 1.7.2 docume...

    Multioutput regression and classification. The estimators provided in this module are meta-estimators: they require a base estimator to be provided in their constructor. The meta-estimator extends ...
    scikit-learn.org/stable/api/sklearn.multioutput.html
    Sat Oct 11 07:51:27 UTC 2025
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  7. sklearn.inspection — scikit-learn 1.7.2 documen...

    Tools for model inspection. User guide. See the Inspection section for further details. Plotting:
    scikit-learn.org/stable/api/sklearn.inspection.html
    Sat Oct 11 07:51:27 UTC 2025
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  8. sklearn.manifold — scikit-learn 1.7.2 documenta...

    Data embedding techniques. User guide. See the Manifold learning section for further details.
    scikit-learn.org/stable/api/sklearn.manifold.html
    Sat Oct 11 07:51:27 UTC 2025
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  9. sklearn.covariance — scikit-learn 1.7.2 documen...

    Methods and algorithms to robustly estimate covariance. They estimate the covariance of features at given sets of points, as well as the precision matrix defined as the inverse of the covariance. C...
    scikit-learn.org/stable/api/sklearn.covariance.html
    Sat Oct 11 07:51:26 UTC 2025
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  10. check_cv — scikit-learn 1.7.2 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version check_cv # sklearn.model_selection. check_cv ( cv = 5...
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.check_cv.html
    Sat Oct 11 07:51:26 UTC 2025
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