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  1. Kernel Approximation — scikit-learn 1.7.0 docum...

    Examples concerning the sklearn.kernel_approximation module. Scalable learning with polynomial kernel approximation
    scikit-learn.org/stable/auto_examples/kernel_approximation/index.html
    Thu Jul 03 11:42:05 UTC 2025
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  2. Feature discretization — scikit-learn 1.7.0 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
    Thu Jul 03 11:42:06 UTC 2025
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  3. Logistic function — scikit-learn 1.7.0 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
    Thu Jul 03 11:42:06 UTC 2025
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  4. Gaussian Mixture Model Ellipsoids — scikit-lear...

    Plot the confidence ellipsoids of a mixture of two Gaussians obtained with Expectation Maximisation ( GaussianMixture class) and Variational Inference ( BayesianGaussianMixture class models with a ...
    scikit-learn.org/stable/auto_examples/mixture/plot_gmm.html
    Thu Jul 03 11:42:05 UTC 2025
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  5. Decision Tree Regression with AdaBoost — scikit...

    A decision tree is boosted using the AdaBoost.R2 1 algorithm on a 1D sinusoidal dataset with a small amount of Gaussian noise. 299 boosts (300 decision trees) is compared with a single decision tre...
    scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_regression.html
    Thu Jul 03 11:42:05 UTC 2025
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  6. Compare cross decomposition methods — scikit-le...

    Simple usage of various cross decomposition algorithms: PLSCanonical, PLSRegression, with multivariate response, a.k.a. PLS2, PLSRegression, with univariate response, a.k.a. PLS1, CCA. Given 2 mult...
    scikit-learn.org/stable/auto_examples/cross_decomposition/plot_compare_cross_decomposition.html
    Thu Jul 03 11:42:06 UTC 2025
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  7. 7. Dataset transformations — scikit-learn 1.7.0...

    scikit-learn provides a library of transformers, which may clean (see Preprocessing data), reduce (see Unsupervised dimensionality reduction), expand (see Kernel Approximation) or generate (see Fea...
    scikit-learn.org/stable/data_transforms.html
    Thu Jul 03 11:42:06 UTC 2025
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  8. img_to_graph — scikit-learn 1.7.0 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version img_to_graph # sklearn.feature_extraction.image. img_...
    scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.image.img_to_graph.html
    Thu Jul 03 11:42:05 UTC 2025
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  9. 12.1. Array API support (experimental) — scikit...

    refer to SciPy’s Array API documentation . Some scikit-learn estimators...
    scikit-learn.org/stable/modules/array_api.html
    Thu Jul 03 11:42:05 UTC 2025
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  10. 9.3. Parallelism, resource management, and conf...

    n_jobs is currently poorly documented. Please help us by improving...explained by this piece of documentation . 9.3.1.3. Parallel NumPy...
    scikit-learn.org/stable/computing/parallelism.html
    Thu Jul 03 11:42:06 UTC 2025
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