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  1. randomized_range_finder — scikit-learn 1.7.0 do...

    Skip to main content Back to top Ctrl + K GitHub Choose version randomized_range_finder # sklearn.utils.extmath. rand...
    scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.randomized_range_finder.html
    Thu Jul 03 11:42:05 UTC 2025
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  2. compute_sample_weight — scikit-learn 1.7.0 docu...

    Skip to main content Back to top Ctrl + K GitHub Choose version compute_sample_weight # sklearn.utils.class_weight. c...
    scikit-learn.org/stable/modules/generated/sklearn.utils.class_weight.compute_sample_weight.html
    Thu Jul 03 11:42:05 UTC 2025
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  3. 3. Model selection and evaluation — scikit-lear...

    Cross-validation: evaluating estimator performance- Computing cross-validated metrics, Cross validation iterators, A note on shuffling, Cross validation and model selection, Permutation test score....
    scikit-learn.org/stable/model_selection.html
    Mon Jul 07 14:36:35 UTC 2025
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  4. Online learning of a dictionary of parts of fac...

    This example uses a large dataset of faces to learn a set of 20 x 20 images patches that constitute faces. From the programming standpoint, it is interesting because it shows how to use the online ...
    scikit-learn.org/stable/auto_examples/cluster/plot_dict_face_patches.html
    Mon Jul 07 14:36:35 UTC 2025
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  5. Segmenting the picture of greek coins in region...

    This example uses Spectral clustering on a graph created from voxel-to-voxel difference on an image to break this image into multiple partly-homogeneous regions. This procedure (spectral clustering...
    scikit-learn.org/stable/auto_examples/cluster/plot_coin_segmentation.html
    Mon Jul 07 14:36:35 UTC 2025
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  6. L1 Penalty and Sparsity in Logistic Regression ...

    Comparison of the sparsity (percentage of zero coefficients) of solutions when L1, L2 and Elastic-Net penalty are used for different values of C. We can see that large values of C give more freedom...
    scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_l1_l2_sparsity.html
    Mon Jul 07 14:36:32 UTC 2025
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  7. Non-negative least squares — scikit-learn 1.7.0...

    In this example, we fit a linear model with positive constraints on the regression coefficients and compare the estimated coefficients to a classic linear regression. Generate some random data Spli...
    scikit-learn.org/stable/auto_examples/linear_model/plot_nnls.html
    Mon Jul 07 14:36:32 UTC 2025
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  8. Scalable learning with polynomial kernel approx...

    This example illustrates the use of PolynomialCountSketch to efficiently generate polynomial kernel feature-space approximations. This is used to train linear classifiers that approximate the accur...
    scikit-learn.org/stable/auto_examples/kernel_approximation/plot_scalable_poly_kernels.html
    Mon Jul 07 14:36:32 UTC 2025
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  9. compute_class_weight — scikit-learn 1.7.0 docum...

    Skip to main content Back to top Ctrl + K GitHub Choose version compute_class_weight # sklearn.utils.class_weight. co...
    scikit-learn.org/stable/modules/generated/sklearn.utils.class_weight.compute_class_weight.html
    Mon Jul 07 14:36:32 UTC 2025
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  10. Dimensionality Reduction with Neighborhood Comp...

    Sample usage of Neighborhood Components Analysis for dimensionality reduction. This example compares different (linear) dimensionality reduction methods applied on the Digits data set. The data set...
    scikit-learn.org/stable/auto_examples/neighbors/plot_nca_dim_reduction.html
    Mon Jul 07 14:36:32 UTC 2025
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