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  1. mutual_info_classif — scikit-learn 1.7.1 docume...

    means 1 unless in a joblib.parallel_backend context. -1 means...References [ 1 ] Mutual Information on Wikipedia. [ 2 ] ( 1 , 2 ) A....
    scikit-learn.org/stable/modules/generated/sklearn.feature_selection.mutual_info_classif.html
    Sat Aug 02 00:15:38 UTC 2025
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  2. Effect of transforming the targets in regressio...

    subplots ( 1 , 2 ) ax0 . hist ( y , bins =...suptitle ( "Synthetic data" , y = 1.05 ) plt . tight_layout () X_train...
    scikit-learn.org/stable/auto_examples/compose/plot_transformed_target.html
    Sat Aug 02 00:15:35 UTC 2025
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  3. __sklearn_is_fitted__ as Developer API — scikit...

    scikit-learn 1.6 Release Highlights for scikit-learn 1.6 Metadata...__init__ ( self , parameter = 1 ): self . parameter = parameter...
    scikit-learn.org/stable/auto_examples/developing_estimators/sklearn_is_fitted.html
    Sat Aug 02 00:15:35 UTC 2025
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  4. 3.2. Tuning the hyper-parameters of an estimato...

    loguniform(1, 100) can be used instead of [1, 10, 100] . Mirroring...reference to the literature. 3.2.1. Exhaustive Grid Search # The...
    scikit-learn.org/stable/modules/grid_search.html
    Sat Aug 02 00:15:38 UTC 2025
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  5. Bisecting K-Means and Regular K-Means Performan...

    1 ], s = 10 , c = algo . labels_...centers [:, 0 ], centers [:, 1 ], c = "r" , s = 20 ) axs [ j...
    scikit-learn.org/stable/auto_examples/cluster/plot_bisect_kmeans.html
    Sat Aug 02 00:15:35 UTC 2025
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  6. load_sample_image — scikit-learn 1.7.1 document...

    Skip to main content Back to top Ctrl + K GitHub Choose version load_sample_image # sklearn.datasets. load_sample_ima...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.load_sample_image.html
    Sat Aug 02 00:15:36 UTC 2025
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  7. sklearn.naive_bayes — scikit-learn 1.7.1 docume...

    Naive Bayes algorithms. These are supervised learning methods based on applying Bayes’ theorem with strong (naive) feature independence assumptions. User guide. See the Naive Bayes section for furt...
    scikit-learn.org/stable/api/sklearn.naive_bayes.html
    Sat Aug 02 00:15:38 UTC 2025
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  8. sklearn.kernel_approximation — scikit-learn 1.7...

    Approximate kernel feature maps based on Fourier transforms and count sketches. User guide. See the Kernel Approximation section for further details.
    scikit-learn.org/stable/api/sklearn.kernel_approximation.html
    Sat Aug 02 00:15:38 UTC 2025
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  9. sklearn.random_projection — scikit-learn 1.7.1 ...

    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
    Sat Aug 02 00:15:36 UTC 2025
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  10. Examples based on real world datasets — scikit-...

    Applications to real world problems with some medium sized datasets or interactive user interface. Compressive sensing: tomography reconstruction with L1 prior (Lasso) Faces recognition example usi...
    scikit-learn.org/stable/auto_examples/applications/index.html
    Sat Aug 02 00:15:37 UTC 2025
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