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  1. coverage_error — scikit-learn 1.5.2 documentation

    y_true = [[ 1 , 0 , 0 ], [ 0 , 1 , 1 ]] >>> y_score = [[ 1 , 0 , 0...0 ], [ 0 , 1 , 1 ]] >>> coverage_error ( y_true , y_score ) np.float64(1.5)...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.coverage_error.html
    Fri Nov 01 07:27:38 UTC 2024
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  2. Miscellaneous — scikit-learn 1.5.2 documentation

    Miscellaneous and introductory examples for scikit-learn. Advanced Plotting With Partial Dependence Comparing anomaly detection algorithms for outlier detection on toy datasets Comparison of kernel...
    scikit-learn.org/stable/auto_examples/miscellaneous/index.html
    Fri Nov 01 07:27:41 UTC 2024
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  3. FitFailedWarning — scikit-learn 1.5.2 documenta...

    Skip to main content Back to top Ctrl + K GitHub FitFailedWarning # exception sklearn.exceptions. FitFailedWarning [s...
    scikit-learn.org/stable/modules/generated/sklearn.exceptions.FitFailedWarning.html
    Fri Nov 01 07:27:40 UTC 2024
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  4. Biclustering — scikit-learn 1.5.2 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
    Fri Nov 01 07:27:39 UTC 2024
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  5. Calibration — scikit-learn 1.5.2 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
    Fri Nov 01 07:27:41 UTC 2024
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  6. DataDimensionalityWarning — scikit-learn 1.5.2 ...

    Skip to main content Back to top Ctrl + K GitHub DataDimensionalityWarning # exception sklearn.exceptions. DataDimens...
    scikit-learn.org/stable/modules/generated/sklearn.exceptions.DataDimensionalityWarning.html
    Fri Nov 01 07:27:38 UTC 2024
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  7. make_friedman1 — scikit-learn 1.5.2 documentation

    Annals of Statistics 19 (1), pages 1-67, 1991. [ 2 ] L. Breiman,...[source] # Generate the “Friedman #1” regression problem. This dataset...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman1.html
    Fri Nov 01 07:27:38 UTC 2024
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  8. Gradient Boosting regression — scikit-learn 1.5...

    subplot ( 1 , 1 , 1 ) plt . title ( "Deviance"...12 , 6 )) plt . subplot ( 1 , 2 , 1 ) plt . barh ( pos , feature_importance...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regression.html
    Fri Nov 01 07:27:40 UTC 2024
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  9. Robust linear model estimation using RANSAC — s...

    n_features = 1 , n_informative = 1 , noise = 10 , coef...normal ( size = ( n_outliers , 1 )) y [: n_outliers ] = - 3 + 10...
    scikit-learn.org/stable/auto_examples/linear_model/plot_ransac.html
    Fri Nov 01 07:27:41 UTC 2024
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  10. dcg_score — scikit-learn 1.5.2 documentation

    asarray ([[ 1 , 0 , 0 , 0 , 1 ]]) >>> # by default ties...to have a score between 0 and 1. References Wikipedia entry for...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.dcg_score.html
    Fri Nov 01 07:27:39 UTC 2024
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