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  1. pairwise_distances_argmin_min — scikit-learn 1....

    ‘yule’] See the documentation for scipy.spatial.distance...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise_distances_argmin_min.html
    Sat Apr 19 00:31:21 UTC 2025
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  2. 11.1. Array API support (experimental) — scikit...

    refer to SciPy’s Array API documentation . Some scikit-learn estimators...
    scikit-learn.org/stable/modules/array_api.html
    Sat Apr 19 00:31:22 UTC 2025
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  3. 8.3. Parallelism, resource management, and conf...

    n_jobs is currently poorly documented. Please help us by improving...explained by this piece of documentation . 8.3.1.3. Parallel NumPy...
    scikit-learn.org/stable/computing/parallelism.html
    Sat Apr 19 00:31:22 UTC 2025
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  4. Sparse inverse covariance estimation — scikit-l...

    Using the GraphicalLasso estimator to learn a covariance and sparse precision from a small number of samples. To estimate a probabilistic model (e.g. a Gaussian model), estimating the precision mat...
    scikit-learn.org/stable/auto_examples/covariance/plot_sparse_cov.html
    Sat Apr 19 00:31:22 UTC 2025
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  5. SGD: Weighted samples — scikit-learn 1.6.1 docu...

    Plot decision function of a weighted dataset, where the size of points is proportional to its weight. Total running time of the script:(0 minutes 0.077 seconds) Launch binder Launch JupyterLite Dow...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_weighted_samples.html
    Sat Apr 19 00:31:22 UTC 2025
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  6. Gaussian Process for Machine Learning — scikit-...

    Examples concerning the sklearn.gaussian_process module. Ability of Gaussian process regression (GPR) to estimate data noise-level Comparison of kernel ridge and Gaussian process regression Forecas...
    scikit-learn.org/stable/auto_examples/gaussian_process/index.html
    Sat Apr 19 00:31:21 UTC 2025
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  7. Two-class AdaBoost — scikit-learn 1.6.1 documen...

    This example fits an AdaBoosted decision stump on a non-linearly separable classification dataset composed of two “Gaussian quantiles” clusters (see sklearn.datasets.make_gaussian_quantiles) and pl...
    scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_twoclass.html
    Sat Apr 19 00:31:22 UTC 2025
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  8. SVM Tie Breaking Example — scikit-learn 1.6.1 d...

    Tie breaking is costly if decision_function_shape='ovr', and therefore it is not enabled by default. This example illustrates the effect of the break_ties parameter for a multiclass classification ...
    scikit-learn.org/stable/auto_examples/svm/plot_svm_tie_breaking.html
    Sat Apr 19 00:31:22 UTC 2025
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  9. Early stopping in Gradient Boosting — scikit-le...

    Gradient Boosting is an ensemble technique that combines multiple weak learners, typically decision trees, to create a robust and powerful predictive model. It does so in an iterative fashion, wher...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_early_stopping.html
    Sat Apr 19 00:31:22 UTC 2025
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  10. A demo of the Spectral Biclustering algorithm —...

    This example demonstrates how to generate a checkerboard dataset and bicluster it using the SpectralBiclustering algorithm. The spectral biclustering algorithm is specifically designed to cluster d...
    scikit-learn.org/stable/auto_examples/bicluster/plot_spectral_biclustering.html
    Sat Apr 19 00:31:21 UTC 2025
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