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  1. Version 0.13 — scikit-learn 1.7.2 documentation

    Jackman 1 Subhodeep Moitra 1 bob 1 dengemann 1 emanuele 1 x006 On...Coelho 1 Miroslav Batchkarov 1 Pavel 1 Sebastian Berg 1 Shaun...
    scikit-learn.org/stable/whats_new/v0.13.html
    Thu Oct 30 14:56:38 UTC 2025
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  2. Decision Tree Regression with AdaBoost — scikit...

    regr_1 . fit ( X , y ) regr_2 . fit ( X , y ) y_1 = regr_1 . predict...X , y_1 , color = colors [ 1 ], label = "n_estimators=1" , linewidth...
    scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_regression.html
    Thu Oct 30 14:56:39 UTC 2025
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  3. _safe_indexing — scikit-learn 1.7.2 documentation

    array([1, 2]) >>> _safe_indexing ( data , 0 , axis = 1 ) # select...integer are supported. If axis=1 : to select a single column, indices...
    scikit-learn.org/stable/modules/generated/sklearn.utils._safe_indexing.html
    Mon Oct 20 15:12:26 UTC 2025
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  4. img_to_graph — scikit-learn 1.7.2 documentation

    1], [0, 0, 0, 1], [0, 1, 1, 1]]) On this page...np . array ([[ 0 , 0 ], [ 0 , 1 ]]) >>> img_to_graph ( img , return_as...
    scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.image.img_to_graph.html
    Thu Oct 30 14:56:39 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
    Thu Oct 30 14:56:38 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
    Thu Oct 30 14:56:37 UTC 2025
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  7. 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
    Thu Oct 30 14:56:38 UTC 2025
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  8. 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
    Thu Oct 30 14:56:38 UTC 2025
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  9. 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
    Thu Oct 30 14:56:38 UTC 2025
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  10. 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
    Thu Oct 30 14:56:38 UTC 2025
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