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  1. 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 Oct 18 13:52:22 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 Oct 18 13:52:20 UTC 2025
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  3. 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 Oct 18 13:52:20 UTC 2025
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  4. 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 Oct 18 13:52:22 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 Oct 18 13:52:22 UTC 2025
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  6. 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 Oct 18 13:52:22 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 Oct 18 13:52:22 UTC 2025
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  8. Novelty detection with Local Outlier Factor (LO...

    n_neighbors) is typically set 1) greater than the minimum number...novelty = True , contamination = 0.1 ) clf . fit ( X_train ) # DO NOT...
    scikit-learn.org/stable/auto_examples/neighbors/plot_lof_novelty_detection.html
    Sat Oct 18 13:52:23 UTC 2025
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  9. Visualizing cross-validation behavior in scikit...

    scikit-learn 1.4 Release Highlights for scikit-learn 1.4 Gallery...10 ) percentiles_classes = [ 0.1 , 0.3 , 0.6 ] y = np . hstack...
    scikit-learn.org/stable/auto_examples/model_selection/plot_cv_indices.html
    Sat Oct 18 13:52:22 UTC 2025
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  10. 13. Choosing the right estimator — scikit-learn...

    Often the hardest part of solving a machine learning problem can be finding the right estimator for the job. Different estimators are better suited for different types of data and different problem...
    scikit-learn.org/stable/machine_learning_map.html
    Sat Oct 18 13:52:20 UTC 2025
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