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  1. fetch_california_housing — scikit-learn 1.7.1 d...

    Gallery examples: Comparing Random Forests and Histogram Gradient Boosting models Early stopping in Gradient Boosting Imputing missing values with variants of IterativeImputer Imputing missing valu...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_california_housing.html
    Sat Aug 23 16:32:03 UTC 2025
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  2. 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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  3. multilabel_confusion_matrix — scikit-learn 1.7....

    Skip to main content Back to top Ctrl + K GitHub Choose version multilabel_confusion_matrix # sklearn.metrics. multil...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.multilabel_confusion_matrix.html
    Sat Aug 23 16:32:04 UTC 2025
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  4. mean_absolute_error — scikit-learn 1.7.1 docume...

    Gallery examples: Lagged features for time series forecasting Poisson regression and non-normal loss Quantile regression Tweedie regression on insurance claims
    scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html
    Sat Aug 23 16:32:04 UTC 2025
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  5. mean_gamma_deviance — scikit-learn 1.7.1 docume...

    Skip to main content Back to top Ctrl + K GitHub Choose version mean_gamma_deviance # sklearn.metrics. mean_gamma_dev...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_gamma_deviance.html
    Sat Aug 23 16:32:04 UTC 2025
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  6. mean_squared_error — scikit-learn 1.7.1 documen...

    Gallery examples: Model Complexity Influence Early stopping in Gradient Boosting Prediction Intervals for Gradient Boosting Regression Gradient Boosting regression Ordinary Least Squares and Ridge ...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html
    Sat Aug 23 16:32:03 UTC 2025
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  7. sklearn.kernel_approximation — scikit-learn 1.7...

    Approximate kernel feature maps based on Fourier transforms and count sketches. User guide. See the Kernel Approximation section for further details.
    scikit-learn.org/stable/api/sklearn.kernel_approximation.html
    Sat Aug 23 16:32:04 UTC 2025
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  8. Crafting a minimal reproducer for scikit-learn ...

    such as this StackOverflow document or this blogpost by Matthew...
    scikit-learn.org/stable/developers/minimal_reproducer.html
    Fri Aug 22 18:00:29 UTC 2025
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  9. Shrinkage covariance estimation: LedoitWolf vs ...

    When working with covariance estimation, the usual approach is to use a maximum likelihood estimator, such as the EmpiricalCovariance. It is unbiased, i.e. it converges to the true (population) cov...
    scikit-learn.org/stable/auto_examples/covariance/plot_covariance_estimation.html
    Sat Aug 23 16:32:03 UTC 2025
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  10. estimator_html_repr — scikit-learn 1.7.1 docume...

    Skip to main content Back to top Ctrl + K GitHub Choose version estimator_html_repr # sklearn.utils. estimator_html_r...
    scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_html_repr.html
    Sat Aug 16 15:30:00 UTC 2025
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