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  1. make_s_curve — scikit-learn 1.7.2 documentation

    Gallery examples: Comparison of Manifold Learning methods t-SNE: The effect of various perplexity values on the shape
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_s_curve.html
    Sat Nov 01 09:15:33 UTC 2025
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  2. enable_iterative_imputer — scikit-learn 1.7.2 d...

    Enables IterativeImputer The API and results of this estimator might change without any deprecation cycle. Importing this file dynamically sets IterativeImputer as an attribute of the impute module:
    scikit-learn.org/stable/modules/generated/sklearn.experimental.enable_iterative_imputer.html
    Sat Nov 01 09:15:33 UTC 2025
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  3. load_sample_images — scikit-learn 1.7.2 documen...

    Skip to main content Back to top Ctrl + K GitHub Choose version load_sample_images # sklearn.datasets. load_sample_im...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.load_sample_images.html
    Sat Nov 01 09:15:33 UTC 2025
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  4. sklearn.feature_selection — scikit-learn 1.7.2 ...

    Feature selection algorithms. These include univariate filter selection methods and the recursive feature elimination algorithm. User guide. See the Feature selection section for further details.
    scikit-learn.org/stable/api/sklearn.feature_selection.html
    Sat Nov 01 09:15:33 UTC 2025
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  5. check_random_state — scikit-learn 1.7.2 documen...

    Gallery examples: Empirical evaluation of the impact of k-means initialization MNIST classification using multinomial logistic + L1 Manifold Learning methods on a severed sphere Isotonic Regression...
    scikit-learn.org/stable/modules/generated/sklearn.utils.check_random_state.html
    Sat Nov 01 09:15:33 UTC 2025
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  6. sklearn.model_selection — scikit-learn 1.7.2 do...

    Tools for model selection, such as cross validation and hyper-parameter tuning. User guide. See the Cross-validation: evaluating estimator performance, Tuning the hyper-parameters of an estimator, ...
    scikit-learn.org/stable/api/sklearn.model_selection.html
    Sat Nov 01 09:15:32 UTC 2025
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  7. get_data_home — scikit-learn 1.7.2 documentation

    Gallery examples: Out-of-core classification of text documents
    scikit-learn.org/stable/modules/generated/sklearn.datasets.get_data_home.html
    Sat Nov 01 09:15:34 UTC 2025
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  8. sklearn.neural_network — scikit-learn 1.7.2 doc...

    Models based on neural networks. User guide. See the Neural network models (supervised) and Neural network models (unsupervised) sections for further details.
    scikit-learn.org/stable/api/sklearn.neural_network.html
    Sat Nov 01 09:15:33 UTC 2025
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  9. 7.8. Pairwise metrics, Affinities and Kernels —...

    for choosing gamma is 1 / num_features S = 1. / (D / np.max(D))...>>> Y = np . array ([[ 1 , 0 ], [ 2 , 1 ]]) >>> pairwise_distances...
    scikit-learn.org/stable/modules/metrics.html
    Sat Nov 01 09:15:34 UTC 2025
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  10. ブースト検索

    りんご ^ 100 みかん ブースト値は 1 以上の整数を指定します。...
    fess.codelibs.org/ja/15.2/user/search-boost.html
    Fri Oct 24 02:40:35 UTC 2025
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