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  1. Non-negative least squares — scikit-learn 1.7.0...

    In this example, we fit a linear model with positive constraints on the regression coefficients and compare the estimated coefficients to a classic linear regression. Generate some random data Spli...
    scikit-learn.org/stable/auto_examples/linear_model/plot_nnls.html
    Fri Jul 11 17:08:39 UTC 2025
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  2. dump_svmlight_file — scikit-learn 1.7.0 documen...

    Skip to main content Back to top Ctrl + K GitHub Choose version dump_svmlight_file # sklearn.datasets. dump_svmlight_...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.dump_svmlight_file.html
    Fri Jul 11 17:08:39 UTC 2025
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  3. clear_data_home — scikit-learn 1.7.0 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version clear_data_home # sklearn.datasets. clear_data_home (...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.clear_data_home.html
    Fri Jul 11 17:08:39 UTC 2025
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  4. make_spd_matrix — scikit-learn 1.7.0 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version make_spd_matrix # sklearn.datasets. make_spd_matrix (...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_spd_matrix.html
    Fri Jul 11 17:08:39 UTC 2025
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  5. sklearn.discriminant_analysis — scikit-learn 1....

    Linear and quadratic discriminant analysis. User guide. See the Linear and Quadratic Discriminant Analysis section for further details.
    scikit-learn.org/stable/api/sklearn.discriminant_analysis.html
    Fri Jul 11 17:08:41 UTC 2025
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  6. sklearn.semi_supervised — scikit-learn 1.7.0 do...

    Semi-supervised learning algorithms. These algorithms utilize small amounts of labeled data and large amounts of unlabeled data for classification tasks. User guide. See the Semi-supervised learnin...
    scikit-learn.org/stable/api/sklearn.semi_supervised.html
    Fri Jul 11 17:08:38 UTC 2025
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  7. sklearn.linear_model — scikit-learn 1.7.0 docum...

    A variety of linear models. User guide. See the Linear Models section for further details. The following subsections are only rough guidelines: the same estimator can fall into multiple categories,...
    scikit-learn.org/stable/api/sklearn.linear_model.html
    Fri Jul 11 17:08:39 UTC 2025
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  8. get_scorer_names — scikit-learn 1.7.0 documenta...

    Skip to main content Back to top Ctrl + K GitHub Choose version get_scorer_names # sklearn.metrics. get_scorer_names ...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.get_scorer_names.html
    Fri Jul 11 17:08:41 UTC 2025
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  9. sklearn.cross_decomposition — scikit-learn 1.7....

    Algorithms for cross decomposition. User guide. See the Cross decomposition section for further details.
    scikit-learn.org/stable/api/sklearn.cross_decomposition.html
    Fri Jul 11 17:08:41 UTC 2025
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  10. Image denoising using kernel PCA — scikit-learn...

    4 of [ 1 ] . References # Authors: The...pixel values are in the range (0, 1). import numpy as np from sklearn.datasets...
    scikit-learn.org/stable/auto_examples/applications/plot_digits_denoising.html
    Fri Jul 11 17:08:41 UTC 2025
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