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  1. Inductive Clustering — scikit-learn 1.7.2 docum...

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    scikit-learn.org/stable/auto_examples/cluster/plot_inductive_clustering.html
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  2. Ability of Gaussian process regression (GPR) to...

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    scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_noisy.html
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  3. Robust covariance estimation and Mahalanobis di...

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    scikit-learn.org/stable/auto_examples/covariance/plot_mahalanobis_distances.html
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  4. check_X_y — scikit-learn 1.7.2 documentation

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    scikit-learn.org/stable/modules/generated/sklearn.utils.check_X_y.html
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  5. Hashing feature transformation using Totally Ra...

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    scikit-learn.org/stable/auto_examples/ensemble/plot_random_forest_embedding.html
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  6. Lasso model selection via information criteria ...

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    scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_lars_ic.html
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  7. Novelty detection with Local Outlier Factor (LO...

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    scikit-learn.org/stable/auto_examples/neighbors/plot_lof_novelty_detection.html
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  8. Test with permutations the significance of a cl...

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    scikit-learn.org/stable/auto_examples/model_selection/plot_permutation_tests_for_classification.html
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  9. Sparse coding with a precomputed dictionary — s...

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    scikit-learn.org/stable/auto_examples/decomposition/plot_sparse_coding.html
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  10. Feature importances with a forest of trees — sc...

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    scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances.html
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