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  1. Nested versus non-nested cross-validation — sci...

    This example compares non-nested and nested cross-validation strategies on a classifier of the iris data set. Nested cross-validation (CV) is often used to train a model in which hyperparameters al...
    scikit-learn.org/stable/auto_examples/model_selection/plot_nested_cross_validation_iris.html
    Mon Mar 23 20:39:22 UTC 2026
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  2. Outlier detection with Local Outlier Factor (LO...

    The Local Outlier Factor (LOF) algorithm is an unsupervised anomaly detection method which computes the local density deviation of a given data point with respect to its neighbors. It considers as ...
    scikit-learn.org/stable/auto_examples/neighbors/plot_lof_outlier_detection.html
    Mon Mar 23 20:39:22 UTC 2026
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  3. Plot different SVM classifiers in the iris data...

    Comparison of different linear SVM classifiers on a 2D projection of the iris dataset. We only consider the first 2 features of this dataset: Sepal length, Sepal width. This example shows how to pl...
    scikit-learn.org/stable/auto_examples/svm/plot_iris_svc.html
    Mon Mar 23 20:39:22 UTC 2026
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  4. Shrinkage covariance estimation: LedoitWolf vs ...

    When working with covariance estimation, the usual approach is to use a maximum likelihood estimator, such as the EmpiricalCovariance. It is unbiased, i.e. it converges to the true (population) cov...
    scikit-learn.org/stable/auto_examples/covariance/plot_covariance_estimation.html
    Mon Mar 23 20:39:20 UTC 2026
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  5. Concentration Prior Type Analysis of Variation ...

    This example plots the ellipsoids obtained from a toy dataset (mixture of three Gaussians) fitted by the BayesianGaussianMixture class models with a Dirichlet distribution prior ( weight_concentrat...
    scikit-learn.org/stable/auto_examples/mixture/plot_concentration_prior.html
    Mon Mar 23 20:39:20 UTC 2026
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  6. Demonstration of multi-metric evaluation on cro...

    Multiple metric parameter search can be done by setting the scoring parameter to a list of metric scorer names or a dict mapping the scorer names to the scorer callables. The scores of all the scor...
    scikit-learn.org/stable/auto_examples/model_selection/plot_multi_metric_evaluation.html
    Mon Mar 23 20:39:22 UTC 2026
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  7. Linear and Quadratic Discriminant Analysis with...

    This example plots the covariance ellipsoids of each class and the decision boundary learned by LinearDiscriminantAnalysis(LDA) and QuadraticDiscriminantAnalysis(QDA). The ellipsoids display the do...
    scikit-learn.org/stable/auto_examples/classification/plot_lda_qda.html
    Mon Mar 23 20:39:21 UTC 2026
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  8. Release Highlights for scikit-learn 1.3 — sciki...

    We are pleased to announce the release of scikit-learn 1.3! Many bug fixes and improvements were added, as well as some new key features. We detail below a few of the major features of this release...
    scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_3_0.html
    Mon Mar 23 20:39:20 UTC 2026
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  9. Comparison of the K-Means and MiniBatchKMeans c...

    We want to compare the performance of the MiniBatchKMeans and KMeans: the MiniBatchKMeans is faster, but gives slightly different results (see Mini Batch K-Means). We will cluster a set of data, fi...
    scikit-learn.org/stable/auto_examples/cluster/plot_mini_batch_kmeans.html
    Mon Mar 23 20:39:20 UTC 2026
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  10. Robust covariance estimation and Mahalanobis di...

    This example shows covariance estimation with Mahalanobis distances on Gaussian distributed data. For Gaussian distributed data, the distance of an observation x_i to the mode of the distribution c...
    scikit-learn.org/stable/auto_examples/covariance/plot_mahalanobis_distances.html
    Mon Mar 23 20:39:22 UTC 2026
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