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  1. inplace_swap_column — scikit-learn 1.7.1 docume...

    Skip to main content Back to top Ctrl + K GitHub Choose version inplace_swap_column # sklearn.utils.sparsefuncs. inpl...
    scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.inplace_swap_column.html
    Fri Aug 22 18:00:33 UTC 2025
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  2. safe_sparse_dot — scikit-learn 1.7.1 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version safe_sparse_dot # sklearn.utils.extmath. safe_sparse_...
    scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.safe_sparse_dot.html
    Fri Aug 22 18:00:29 UTC 2025
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  3. estimator_checks_generator — scikit-learn 1.7.1...

    Skip to main content Back to top Ctrl + K GitHub Choose version estimator_checks_generator # sklearn.utils.estimator_...
    scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_checks.estimator_checks_generat...
    Fri Aug 22 18:00:33 UTC 2025
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  4. inplace_row_scale — scikit-learn 1.7.1 document...

    Skip to main content Back to top Ctrl + K GitHub Choose version inplace_row_scale # sklearn.utils.sparsefuncs. inplac...
    scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.inplace_row_scale.html
    Fri Aug 22 18:00:34 UTC 2025
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  5. Prediction Intervals for Gradient Boosting Regr...

    This example shows how quantile regression can be used to create prediction intervals. See Features in Histogram Gradient Boosting Trees for an example showcasing some other features of HistGradien...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_quantile.html
    Sat Aug 23 16:32:03 UTC 2025
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  6. Gaussian Mixture Model Sine Curve — scikit-lear...

    This example demonstrates the behavior of Gaussian mixture models fit on data that was not sampled from a mixture of Gaussian random variables. The dataset is formed by 100 points loosely spaced fo...
    scikit-learn.org/stable/auto_examples/mixture/plot_gmm_sin.html
    Sat Aug 23 16:32:04 UTC 2025
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  7. Lagged features for time series forecasting — s...

    This example demonstrates how Polars-engineered lagged features can be used for time series forecasting with HistGradientBoostingRegressor on the Bike Sharing Demand dataset. See the example on Tim...
    scikit-learn.org/stable/auto_examples/applications/plot_time_series_lagged_features.html
    Sat Aug 23 16:32:04 UTC 2025
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  8. Imputing missing values with variants of Iterat...

    The IterativeImputer class is very flexible - it can be used with a variety of estimators to do round-robin regression, treating every variable as an output in turn. In this example we compare some...
    scikit-learn.org/stable/auto_examples/impute/plot_iterative_imputer_variants_comparison.html
    Sat Aug 23 16:32:03 UTC 2025
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  9. Robust vs Empirical covariance estimate — sciki...

    The usual covariance maximum likelihood estimate is very sensitive to the presence of outliers in the data set. In such a case, it would be better to use a robust estimator of covariance to guarant...
    scikit-learn.org/stable/auto_examples/covariance/plot_robust_vs_empirical_covariance.html
    Sat Aug 23 16:32:03 UTC 2025
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  10. label_ranking_loss — scikit-learn 1.7.1 documen...

    Skip to main content Back to top Ctrl + K GitHub Choose version label_ranking_loss # sklearn.metrics. label_ranking_l...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.label_ranking_loss.html
    Sat Aug 23 16:32:04 UTC 2025
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