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  1. Kernel Density Estimation — scikit-learn 1.7.2 ...

    This example shows how kernel density estimation (KDE), a powerful non-parametric density estimation technique, can be used to learn a generative model for a dataset. With this generative model in ...
    scikit-learn.org/stable/auto_examples/neighbors/plot_digits_kde_sampling.html
    Thu Sep 18 09:36:17 UTC 2025
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  2. r_regression — scikit-learn 1.7.2 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version r_regression # sklearn.feature_selection. r_regressio...
    scikit-learn.org/stable/modules/generated/sklearn.feature_selection.r_regression.html
    Thu Sep 18 09:36:17 UTC 2025
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  3. load_digits — scikit-learn 1.7.2 documentation

    Gallery examples: Recognizing hand-written digits Feature agglomeration Various Agglomerative Clustering on a 2D embedding of digits A demo of K-Means clustering on the handwritten digits data Sele...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.load_digits.html
    Thu Sep 18 09:36:17 UTC 2025
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  4. Support Vector Machines — scikit-learn 1.7.2 do...

    Examples concerning the sklearn.svm module. One-class SVM with non-linear kernel (RBF) Plot classification boundaries with different SVM Kernels Plot different SVM classifiers in the iris dataset P...
    scikit-learn.org/stable/auto_examples/svm/index.html
    Thu Sep 18 09:36:17 UTC 2025
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  5. check_memory — scikit-learn 1.7.2 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version check_memory # sklearn.utils.validation. check_memory...
    scikit-learn.org/stable/modules/generated/sklearn.utils.validation.check_memory.html
    Thu Sep 18 09:36:18 UTC 2025
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  6. permutation_importance — scikit-learn 1.7.2 doc...

    Gallery examples: Feature importances with a forest of trees Gradient Boosting regression Permutation Importance vs Random Forest Feature Importance (MDI) Permutation Importance with Multicollinear...
    scikit-learn.org/stable/modules/generated/sklearn.inspection.permutation_importance.html
    Thu Sep 18 09:36:18 UTC 2025
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  7. Missing Value Imputation — scikit-learn 1.7.2 d...

    Examples concerning the sklearn.impute module. Imputing missing values before building an estimator Imputing missing values with variants of IterativeImputer
    scikit-learn.org/stable/auto_examples/impute/index.html
    Thu Sep 18 09:36:17 UTC 2025
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  8. sklearn.exceptions — scikit-learn 1.7.2 documen...

    Custom warnings and errors used across scikit-learn.
    scikit-learn.org/stable/api/sklearn.exceptions.html
    Thu Sep 18 09:36:17 UTC 2025
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  9. cosine_similarity — scikit-learn 1.7.2 document...

    Gallery examples: Plot classification boundaries with different SVM Kernels
    scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.cosine_similarity.html
    Thu Sep 18 09:36:17 UTC 2025
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  10. sklearn.experimental — scikit-learn 1.7.2 docum...

    Importable modules that enable the use of experimental features or estimators.
    scikit-learn.org/stable/api/sklearn.experimental.html
    Thu Sep 18 09:36:17 UTC 2025
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