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  1. sklearn.model_selection — scikit-learn 1.8.0 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
    Tue Mar 17 03:44:36 UTC 2026
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  2. sklearn.feature_selection — scikit-learn 1.8.0 ...

    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
    Tue Mar 17 03:44:36 UTC 2026
      13.1K bytes
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  3. sklearn.neural_network — scikit-learn 1.8.0 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
    Tue Mar 17 03:44:36 UTC 2026
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  4. sklearn.experimental — scikit-learn 1.8.0 docum...

    Importable modules that enable the use of experimental features or estimators.
    scikit-learn.org/stable/api/sklearn.experimental.html
    Tue Mar 17 03:44:39 UTC 2026
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  5. sklearn.exceptions — scikit-learn 1.8.0 documen...

    Custom warnings and errors used across scikit-learn.
    scikit-learn.org/stable/api/sklearn.exceptions.html
    Tue Mar 17 03:44:36 UTC 2026
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  6. 3.2. Tuning the hyper-parameters of an estimato...

    coupling parameters from a text documents feature extractor (n-gram...
    scikit-learn.org/stable/modules/grid_search.html
    Tue Mar 17 03:44:39 UTC 2026
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  7. org.springframework.web.servlet.view.document C...

    document Package Hierarchies: All Packages...org.springframework.web.servlet.view.document. AbstractPdfView org.spri...
    docs.spring.io/spring-framework/docs/current/javadoc-api/org/springframework/web/servlet/view/doc...
    Fri Feb 01 00:00:00 UTC 1980
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  8. sklearn.random_projection — scikit-learn ...

    Random projection transformers. Random projections are a simple and computationally efficient way to reduce the dimensionality of the data by trading a controlled amount of accuracy (as additional ...
    scikit-learn.org/stable/api/sklearn.random_projection.html
    Mon Mar 09 16:03:57 UTC 2026
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  9. Compare BIRCH and MiniBatchKMeans — scikit-lear...

    This example compares the timing of BIRCH (with and without the global clustering step) and MiniBatchKMeans on a synthetic dataset having 25,000 samples and 2 features generated using make_blobs. B...
    scikit-learn.org/stable/auto_examples/cluster/plot_birch_vs_minibatchkmeans.html
    Tue Mar 17 03:44:36 UTC 2026
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  10. Semi Supervised Classification — scikit-learn 1...

    Examples concerning the sklearn.semi_supervised module. Decision boundary of semi-supervised classifiers versus SVM on the Iris dataset Effect of varying threshold for self-training Label Propagati...
    scikit-learn.org/stable/auto_examples/semi_supervised/index.html
    Tue Mar 17 03:44:39 UTC 2026
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