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  1. RidgeClassifier — scikit-learn 1.7.2 documentation

    # Classification of text documents using sparse features Classification...Classification of text documents using sparse features On this page...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeClassifier.html
    Fri Oct 10 15:14:35 UTC 2025
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  2. Elasticsearch index engines | App Search docume...

    the original document. Given the following document: { "manager":...engines IMPORTANT : This documentation is no longer updated. Refer...
    www.elastic.co/guide/en/app-search/current/elasticsearch-engines.html
    Tue Jul 29 14:26:41 UTC 2025
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  3. Visualizing the stock market structure — scikit...

    Documentation for GraphicalLassoCV i Fitted...
    scikit-learn.org/stable/auto_examples/applications/plot_stock_market.html
    Fri Oct 10 15:14:33 UTC 2025
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  4. Incremental PCA — scikit-learn 1.7.2 documentation

    Incremental principal component analysis (IPCA) is typically used as a replacement for principal component analysis (PCA) when the dataset to be decomposed is too large to fit in memory. IPCA build...
    scikit-learn.org/stable/auto_examples/decomposition/plot_incremental_pca.html
    Fri Oct 10 15:14:33 UTC 2025
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  5. GMM covariances — scikit-learn 1.7.2 documentation

    Demonstration of several covariances types for Gaussian mixture models. See Gaussian mixture models for more information on the estimator. Although GMM are often used for clustering, we can compare...
    scikit-learn.org/stable/auto_examples/mixture/plot_gmm_covariances.html
    Fri Oct 10 15:14:33 UTC 2025
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  6. Logistic function — scikit-learn 1.7.2 document...

    Shown in the plot is how the logistic regression would, in this synthetic dataset, classify values as either 0 or 1, i.e. class one or two, using the logistic curve. Total running time of the scrip...
    scikit-learn.org/stable/auto_examples/linear_model/plot_logistic.html
    Fri Oct 10 15:14:33 UTC 2025
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  7. Release History — scikit-learn 1.7.2 documentation

    Changelogs and release notes for all scikit-learn releases are linked in this page. Version 1.7- Version 1.7.2, Version 1.7.1, Version 1.7.0., Version 1.6- Version 1.6.1, Version 1.6.0., Version 1....
    scikit-learn.org/stable/whats_new.html
    Fri Oct 10 15:14:33 UTC 2025
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  8. Kernel Approximation — scikit-learn 1.7.2 docum...

    Examples concerning the sklearn.kernel_approximation module. Scalable learning with polynomial kernel approximation
    scikit-learn.org/stable/auto_examples/kernel_approximation/index.html
    Fri Oct 10 15:14:36 UTC 2025
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  9. Classifier comparison — scikit-learn 1.7.2 docu...

    A comparison of several classifiers in scikit-learn on synthetic datasets. The point of this example is to illustrate the nature of decision boundaries of different classifiers. This should be take...
    scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html
    Fri Oct 10 15:14:36 UTC 2025
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  10. Feature discretization — scikit-learn 1.7.2 doc...

    A demonstration of feature discretization on synthetic classification datasets. Feature discretization decomposes each feature into a set of bins, here equally distributed in width. The discrete va...
    scikit-learn.org/stable/auto_examples/preprocessing/plot_discretization_classification.html
    Fri Oct 10 15:14:33 UTC 2025
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