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  1. 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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  2. 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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  3. sklearn.random_projection — scikit-learn 1.7.1 ...

    Random projection transformers. Random projections are a simple and computationally efficient way to reduce the dimensionality of the data by trading a controlled amount of accuracy (as additional ...
    scikit-learn.org/stable/api/sklearn.random_projection.html
    Sat Aug 23 16:32:04 UTC 2025
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  4. 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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  5. 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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  6. 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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  7. 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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  8. 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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  9. 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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  10. load_sample_image — scikit-learn 1.7.1 document...

    Skip to main content Back to top Ctrl + K GitHub Choose version load_sample_image # sklearn.datasets. load_sample_ima...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.load_sample_image.html
    Sat Aug 23 16:32:03 UTC 2025
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