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  1. LeavePOut — scikit-learn 1.7.2 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version LeavePOut # class sklearn.model_selection. LeavePOut ...
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeavePOut.html
    Fri Dec 05 17:52:54 GMT 2025
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  2. sigmoid_kernel — scikit-learn 1.7.2 docum...

    Skip to main content Back to top Ctrl + K GitHub Choose version sigmoid_kernel # sklearn.metrics.pairwise. sigmoid_ke...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.sigmoid_kernel.html
    Fri Dec 05 17:52:54 GMT 2025
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  3. Compressive sensing: tomography reconstruction ...

    This example shows the reconstruction of an image from a set of parallel projections, acquired along different angles. Such a dataset is acquired in computed tomography(CT). Without any prior infor...
    scikit-learn.org/stable/auto_examples/applications/plot_tomography_l1_reconstruction.html
    Fri Dec 05 17:52:54 GMT 2025
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  4. Single estimator versus bagging: bias-variance ...

    This example illustrates and compares the bias-variance decomposition of the expected mean squared error of a single estimator against a bagging ensemble. In regression, the expected mean squared e...
    scikit-learn.org/stable/auto_examples/ensemble/plot_bias_variance.html
    Fri Dec 05 17:52:54 GMT 2025
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  5. Illustration of prior and posterior Gaussian pr...

    This example illustrates the prior and posterior of a GaussianProcessRegressor with different kernels. Mean, standard deviation, and 5 samples are shown for both prior and posterior distributions. ...
    scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_prior_posterior.html
    Fri Dec 05 17:52:54 GMT 2025
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  6. Fitting an Elastic Net with a precomputed Gram ...

    see the documentation for the sample_weight parameter...nbviewer.org. ElasticNet ? Documentation for ElasticNet i Fitted...
    scikit-learn.org/stable/auto_examples/linear_model/plot_elastic_net_precomputed_gram_matrix_with_...
    Fri Dec 05 17:52:54 GMT 2025
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  7. sklearn.preprocessing — scikit-learn 1.7....

    Methods for scaling, centering, normalization, binarization, and more. User guide. See the Preprocessing data section for further details.
    scikit-learn.org/stable/api/sklearn.preprocessing.html
    Thu Dec 04 11:53:53 GMT 2025
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  8. Getting Started — scikit-learn 1.7.2 docu...

    Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. It also provides various tools for model fitting, data preprocessing, model selection, mo...
    scikit-learn.org/stable/getting_started.html
    Fri Dec 05 17:52:54 GMT 2025
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  9. 5. Inspection — scikit-learn 1.7.2 docume...

    Predictive performance is often the main goal of developing machine learning models. Yet summarizing performance with an evaluation metric is often insufficient: it assumes that the evaluation metr...
    scikit-learn.org/stable/inspection.html
    Fri Dec 05 17:52:54 GMT 2025
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  10. Quantile regression — scikit-learn 1.7.2 ...

    This example illustrates how quantile regression can predict non-trivial conditional quantiles. The left figure shows the case when the error distribution is normal, but has non-constant variance, ...
    scikit-learn.org/stable/auto_examples/linear_model/plot_quantile_regression.html
    Fri Dec 05 17:52:55 GMT 2025
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