Full Code of norbusan/scikit-learn for AI

gitextract_8esimy8a/

├── .binder/
│   ├── postBuild
│   └── requirements.txt
├── .circleci/
│   ├── artifact_path
│   └── config.yml
├── .codecov.yml
├── .coveragerc
├── .git-blame-ignore-revs
├── .gitattributes
├── .github/
│   ├── FUNDING.yml
│   ├── ISSUE_TEMPLATE/
│   │   ├── bug_report.yml
│   │   ├── config.yml
│   │   ├── doc_improvement.yml
│   │   └── feature_request.yml
│   ├── PULL_REQUEST_TEMPLATE.md
│   ├── labeler-file-extensions.yml
│   ├── labeler-module.yml
│   ├── scripts/
│   │   └── label_title_regex.py
│   └── workflows/
│       ├── assign.yml
│       ├── check-changelog.yml
│       ├── check-manifest.yml
│       ├── labeler-module.yml
│       ├── labeler-title-regex.yml
│       ├── publish_pypi.yml
│       ├── twitter.yml
│       ├── unassign.yml
│       └── wheels.yml
├── .gitignore
├── .mailmap
├── .pre-commit-config.yaml
├── .travis.yml
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
├── COPYING
├── MANIFEST.in
├── Makefile
├── README.rst
├── SECURITY.md
├── asv_benchmarks/
│   ├── .gitignore
│   ├── asv.conf.json
│   └── benchmarks/
│       ├── __init__.py
│       ├── cluster.py
│       ├── common.py
│       ├── config.json
│       ├── datasets.py
│       ├── decomposition.py
│       ├── ensemble.py
│       ├── linear_model.py
│       ├── manifold.py
│       ├── metrics.py
│       ├── model_selection.py
│       ├── neighbors.py
│       ├── svm.py
│       └── utils.py
├── azure-pipelines.yml
├── benchmarks/
│   ├── .gitignore
│   ├── bench_20newsgroups.py
│   ├── bench_covertype.py
│   ├── bench_feature_expansions.py
│   ├── bench_glm.py
│   ├── bench_glmnet.py
│   ├── bench_hist_gradient_boosting.py
│   ├── bench_hist_gradient_boosting_adult.py
│   ├── bench_hist_gradient_boosting_categorical_only.py
│   ├── bench_hist_gradient_boosting_higgsboson.py
│   ├── bench_hist_gradient_boosting_threading.py
│   ├── bench_isolation_forest.py
│   ├── bench_isotonic.py
│   ├── bench_kernel_pca_solvers_time_vs_n_components.py
│   ├── bench_kernel_pca_solvers_time_vs_n_samples.py
│   ├── bench_lasso.py
│   ├── bench_lof.py
│   ├── bench_mnist.py
│   ├── bench_multilabel_metrics.py
│   ├── bench_online_ocsvm.py
│   ├── bench_plot_fastkmeans.py
│   ├── bench_plot_hierarchical.py
│   ├── bench_plot_incremental_pca.py
│   ├── bench_plot_lasso_path.py
│   ├── bench_plot_neighbors.py
│   ├── bench_plot_nmf.py
│   ├── bench_plot_omp_lars.py
│   ├── bench_plot_parallel_pairwise.py
│   ├── bench_plot_polynomial_kernel_approximation.py
│   ├── bench_plot_randomized_svd.py
│   ├── bench_plot_svd.py
│   ├── bench_plot_ward.py
│   ├── bench_random_projections.py
│   ├── bench_rcv1_logreg_convergence.py
│   ├── bench_saga.py
│   ├── bench_sample_without_replacement.py
│   ├── bench_sgd_regression.py
│   ├── bench_sparsify.py
│   ├── bench_text_vectorizers.py
│   ├── bench_tree.py
│   ├── bench_tsne_mnist.py
│   └── plot_tsne_mnist.py
├── build_tools/
│   ├── Makefile
│   ├── azure/
│   │   ├── install.sh
│   │   ├── install_win.sh
│   │   ├── posix-docker.yml
│   │   ├── posix.yml
│   │   ├── test_docs.sh
│   │   ├── test_docstring.sh
│   │   ├── test_pytest_soft_dependency.sh
│   │   ├── test_script.sh
│   │   ├── upload_codecov.sh
│   │   └── windows.yml
│   ├── circle/
│   │   ├── build_doc.sh
│   │   ├── build_test_arm.sh
│   │   ├── build_test_pypy.sh
│   │   ├── checkout_merge_commit.sh
│   │   ├── linting.sh
│   │   ├── list_versions.py
│   │   └── push_doc.sh
│   ├── codespell_ignore_words.txt
│   ├── generate_authors_table.py
│   ├── github/
│   │   ├── Windows
│   │   ├── build_minimal_windows_image.sh
│   │   ├── build_source.sh
│   │   ├── build_wheels.sh
│   │   ├── check_build_trigger.sh
│   │   ├── check_wheels.py
│   │   ├── repair_windows_wheels.sh
│   │   ├── test_source.sh
│   │   ├── test_wheels.sh
│   │   ├── test_windows_wheels.sh
│   │   ├── upload_anaconda.sh
│   │   └── vendor.py
│   ├── shared.sh
│   └── travis/
│       ├── after_success.sh
│       ├── install.sh
│       ├── install_main.sh
│       ├── install_wheels.sh
│       ├── script.sh
│       ├── test_docs.sh
│       ├── test_script.sh
│       └── test_wheels.sh
├── conftest.py
├── doc/
│   ├── Makefile
│   ├── README.md
│   ├── about.rst
│   ├── authors.rst
│   ├── authors_emeritus.rst
│   ├── binder/
│   │   └── requirements.txt
│   ├── common_pitfalls.rst
│   ├── communication_team.rst
│   ├── computing/
│   │   ├── computational_performance.rst
│   │   ├── parallelism.rst
│   │   └── scaling_strategies.rst
│   ├── computing.rst
│   ├── conf.py
│   ├── conftest.py
│   ├── contents.rst
│   ├── data_transforms.rst
│   ├── datasets/
│   │   ├── loading_other_datasets.rst
│   │   ├── real_world.rst
│   │   ├── sample_generators.rst
│   │   └── toy_dataset.rst
│   ├── datasets.rst
│   ├── developers/
│   │   ├── advanced_installation.rst
│   │   ├── bug_triaging.rst
│   │   ├── contributing.rst
│   │   ├── develop.rst
│   │   ├── index.rst
│   │   ├── maintainer.rst
│   │   ├── performance.rst
│   │   ├── plotting.rst
│   │   ├── tips.rst
│   │   └── utilities.rst
│   ├── faq.rst
│   ├── getting_started.rst
│   ├── glossary.rst
│   ├── governance.rst
│   ├── includes/
│   │   ├── big_toc_css.rst
│   │   └── bigger_toc_css.rst
│   ├── inspection.rst
│   ├── install.rst
│   ├── make.bat
│   ├── model_selection.rst
│   ├── modules/
│   │   ├── biclustering.rst
│   │   ├── calibration.rst
│   │   ├── classes.rst
│   │   ├── clustering.rst
│   │   ├── compose.rst
│   │   ├── covariance.rst
│   │   ├── cross_decomposition.rst
│   │   ├── cross_validation.rst
│   │   ├── decomposition.rst
│   │   ├── density.rst
│   │   ├── ensemble.rst
│   │   ├── feature_extraction.rst
│   │   ├── feature_selection.rst
│   │   ├── gaussian_process.rst
│   │   ├── grid_search.rst
│   │   ├── impute.rst
│   │   ├── isotonic.rst
│   │   ├── kernel_approximation.rst
│   │   ├── kernel_ridge.rst
│   │   ├── lda_qda.rst
│   │   ├── learning_curve.rst
│   │   ├── linear_model.rst
│   │   ├── manifold.rst
│   │   ├── metrics.rst
│   │   ├── mixture.rst
│   │   ├── model_evaluation.rst
│   │   ├── model_persistence.rst
│   │   ├── multiclass.rst
│   │   ├── naive_bayes.rst
│   │   ├── neighbors.rst
│   │   ├── neural_networks_supervised.rst
│   │   ├── neural_networks_unsupervised.rst
│   │   ├── outlier_detection.rst
│   │   ├── partial_dependence.rst
│   │   ├── permutation_importance.rst
│   │   ├── pipeline.rst
│   │   ├── preprocessing.rst
│   │   ├── preprocessing_targets.rst
│   │   ├── random_projection.rst
│   │   ├── semi_supervised.rst
│   │   ├── sgd.rst
│   │   ├── svm.rst
│   │   ├── tree.rst
│   │   └── unsupervised_reduction.rst
│   ├── preface.rst
│   ├── presentations.rst
│   ├── related_projects.rst
│   ├── roadmap.rst
│   ├── sphinxext/
│   │   ├── MANIFEST.in
│   │   ├── add_toctree_functions.py
│   │   ├── custom_references_resolver.py
│   │   ├── doi_role.py
│   │   ├── github_link.py
│   │   └── sphinx_issues.py
│   ├── supervised_learning.rst
│   ├── support.rst
│   ├── templates/
│   │   ├── class.rst
│   │   ├── class_with_call.rst
│   │   ├── deprecated_class.rst
│   │   ├── deprecated_class_with_call.rst
│   │   ├── deprecated_class_without_init.rst
│   │   ├── deprecated_function.rst
│   │   ├── function.rst
│   │   ├── generate_deprecated.sh
│   │   ├── index.html
│   │   ├── numpydoc_docstring.rst
│   │   └── redirects.html
│   ├── testimonials/
│   │   ├── README.txt
│   │   ├── images/
│   │   │   └── Makefile
│   │   └── testimonials.rst
│   ├── themes/
│   │   └── scikit-learn-modern/
│   │       ├── javascript.html
│   │       ├── layout.html
│   │       ├── nav.html
│   │       ├── search.html
│   │       ├── static/
│   │       │   ├── css/
│   │       │   │   └── theme.css
│   │       │   └── js/
│   │       │       └── searchtools.js
│   │       └── theme.conf
│   ├── triage_team.rst
│   ├── tune_toc.rst
│   ├── tutorial/
│   │   ├── basic/
│   │   │   └── tutorial.rst
│   │   ├── common_includes/
│   │   │   └── info.txt
│   │   ├── index.rst
│   │   ├── machine_learning_map/
│   │   │   ├── ML_MAPS_README.txt
│   │   │   ├── index.rst
│   │   │   ├── parse_path.py
│   │   │   ├── pyparsing.py
│   │   │   └── svg2imagemap.py
│   │   ├── statistical_inference/
│   │   │   ├── index.rst
│   │   │   ├── model_selection.rst
│   │   │   ├── putting_together.rst
│   │   │   ├── settings.rst
│   │   │   ├── supervised_learning.rst
│   │   │   └── unsupervised_learning.rst
│   │   └── text_analytics/
│   │       ├── .gitignore
│   │       ├── data/
│   │       │   ├── languages/
│   │       │   │   └── fetch_data.py
│   │       │   ├── movie_reviews/
│   │       │   │   └── fetch_data.py
│   │       │   └── twenty_newsgroups/
│   │       │       └── fetch_data.py
│   │       ├── skeletons/
│   │       │   ├── exercise_01_language_train_model.py
│   │       │   └── exercise_02_sentiment.py
│   │       ├── solutions/
│   │       │   ├── exercise_01_language_train_model.py
│   │       │   ├── exercise_02_sentiment.py
│   │       │   └── generate_skeletons.py
│   │       └── working_with_text_data.rst
│   ├── unsupervised_learning.rst
│   ├── user_guide.rst
│   ├── visualizations.rst
│   ├── whats_new/
│   │   ├── _contributors.rst
│   │   ├── changelog_legend.inc
│   │   ├── older_versions.rst
│   │   ├── v0.13.rst
│   │   ├── v0.14.rst
│   │   ├── v0.15.rst
│   │   ├── v0.16.rst
│   │   ├── v0.17.rst
│   │   ├── v0.18.rst
│   │   ├── v0.19.rst
│   │   ├── v0.20.rst
│   │   ├── v0.21.rst
│   │   ├── v0.22.rst
│   │   ├── v0.23.rst
│   │   ├── v0.24.rst
│   │   ├── v1.0.rst
│   │   └── v1.1.rst
│   └── whats_new.rst
├── examples/
│   ├── README.txt
│   ├── applications/
│   │   ├── README.txt
│   │   ├── plot_cyclical_feature_engineering.py
│   │   ├── plot_digits_denoising.py
│   │   ├── plot_face_recognition.py
│   │   ├── plot_model_complexity_influence.py
│   │   ├── plot_out_of_core_classification.py
│   │   ├── plot_outlier_detection_wine.py
│   │   ├── plot_prediction_latency.py
│   │   ├── plot_species_distribution_modeling.py
│   │   ├── plot_stock_market.py
│   │   ├── plot_tomography_l1_reconstruction.py
│   │   ├── plot_topics_extraction_with_nmf_lda.py
│   │   ├── svm_gui.py
│   │   └── wikipedia_principal_eigenvector.py
│   ├── bicluster/
│   │   ├── README.txt
│   │   ├── plot_bicluster_newsgroups.py
│   │   ├── plot_spectral_biclustering.py
│   │   └── plot_spectral_coclustering.py
│   ├── calibration/
│   │   ├── README.txt
│   │   ├── plot_calibration.py
│   │   ├── plot_calibration_curve.py
│   │   ├── plot_calibration_multiclass.py
│   │   └── plot_compare_calibration.py
│   ├── classification/
│   │   ├── README.txt
│   │   ├── plot_classification_probability.py
│   │   ├── plot_classifier_comparison.py
│   │   ├── plot_digits_classification.py
│   │   ├── plot_lda.py
│   │   └── plot_lda_qda.py
│   ├── cluster/
│   │   ├── README.txt
│   │   ├── plot_adjusted_for_chance_measures.py
│   │   ├── plot_affinity_propagation.py
│   │   ├── plot_agglomerative_clustering.py
│   │   ├── plot_agglomerative_clustering_metrics.py
│   │   ├── plot_agglomerative_dendrogram.py
│   │   ├── plot_birch_vs_minibatchkmeans.py
│   │   ├── plot_cluster_comparison.py
│   │   ├── plot_cluster_iris.py
│   │   ├── plot_coin_segmentation.py
│   │   ├── plot_coin_ward_segmentation.py
│   │   ├── plot_color_quantization.py
│   │   ├── plot_dbscan.py
│   │   ├── plot_dict_face_patches.py
│   │   ├── plot_digits_agglomeration.py
│   │   ├── plot_digits_linkage.py
│   │   ├── plot_face_compress.py
│   │   ├── plot_feature_agglomeration_vs_univariate_selection.py
│   │   ├── plot_inductive_clustering.py
│   │   ├── plot_kmeans_assumptions.py
│   │   ├── plot_kmeans_digits.py
│   │   ├── plot_kmeans_plusplus.py
│   │   ├── plot_kmeans_silhouette_analysis.py
│   │   ├── plot_kmeans_stability_low_dim_dense.py
│   │   ├── plot_linkage_comparison.py
│   │   ├── plot_mean_shift.py
│   │   ├── plot_mini_batch_kmeans.py
│   │   ├── plot_optics.py
│   │   ├── plot_segmentation_toy.py
│   │   └── plot_ward_structured_vs_unstructured.py
│   ├── compose/
│   │   ├── README.txt
│   │   ├── plot_column_transformer.py
│   │   ├── plot_column_transformer_mixed_types.py
│   │   ├── plot_compare_reduction.py
│   │   ├── plot_digits_pipe.py
│   │   ├── plot_feature_union.py
│   │   └── plot_transformed_target.py
│   ├── covariance/
│   │   ├── README.txt
│   │   ├── plot_covariance_estimation.py
│   │   ├── plot_lw_vs_oas.py
│   │   ├── plot_mahalanobis_distances.py
│   │   ├── plot_robust_vs_empirical_covariance.py
│   │   └── plot_sparse_cov.py
│   ├── cross_decomposition/
│   │   ├── README.txt
│   │   ├── plot_compare_cross_decomposition.py
│   │   └── plot_pcr_vs_pls.py
│   ├── datasets/
│   │   ├── README.txt
│   │   ├── plot_digits_last_image.py
│   │   ├── plot_iris_dataset.py
│   │   ├── plot_random_dataset.py
│   │   └── plot_random_multilabel_dataset.py
│   ├── decomposition/
│   │   ├── README.txt
│   │   ├── plot_beta_divergence.py
│   │   ├── plot_faces_decomposition.py
│   │   ├── plot_ica_blind_source_separation.py
│   │   ├── plot_ica_vs_pca.py
│   │   ├── plot_image_denoising.py
│   │   ├── plot_incremental_pca.py
│   │   ├── plot_kernel_pca.py
│   │   ├── plot_pca_3d.py
│   │   ├── plot_pca_iris.py
│   │   ├── plot_pca_vs_fa_model_selection.py
│   │   ├── plot_pca_vs_lda.py
│   │   ├── plot_sparse_coding.py
│   │   └── plot_varimax_fa.py
│   ├── ensemble/
│   │   ├── README.txt
│   │   ├── plot_adaboost_hastie_10_2.py
│   │   ├── plot_adaboost_multiclass.py
│   │   ├── plot_adaboost_regression.py
│   │   ├── plot_adaboost_twoclass.py
│   │   ├── plot_bias_variance.py
│   │   ├── plot_ensemble_oob.py
│   │   ├── plot_feature_transformation.py
│   │   ├── plot_forest_importances.py
│   │   ├── plot_forest_importances_faces.py
│   │   ├── plot_forest_iris.py
│   │   ├── plot_gradient_boosting_categorical.py
│   │   ├── plot_gradient_boosting_early_stopping.py
│   │   ├── plot_gradient_boosting_oob.py
│   │   ├── plot_gradient_boosting_quantile.py
│   │   ├── plot_gradient_boosting_regression.py
│   │   ├── plot_gradient_boosting_regularization.py
│   │   ├── plot_isolation_forest.py
│   │   ├── plot_monotonic_constraints.py
│   │   ├── plot_random_forest_embedding.py
│   │   ├── plot_random_forest_regression_multioutput.py
│   │   ├── plot_stack_predictors.py
│   │   ├── plot_voting_decision_regions.py
│   │   ├── plot_voting_probas.py
│   │   └── plot_voting_regressor.py
│   ├── exercises/
│   │   ├── README.txt
│   │   ├── plot_cv_diabetes.py
│   │   ├── plot_cv_digits.py
│   │   ├── plot_digits_classification_exercise.py
│   │   └── plot_iris_exercise.py
│   ├── feature_selection/
│   │   ├── README.txt
│   │   ├── plot_f_test_vs_mi.py
│   │   ├── plot_feature_selection.py
│   │   ├── plot_feature_selection_pipeline.py
│   │   ├── plot_rfe_digits.py
│   │   ├── plot_rfe_with_cross_validation.py
│   │   └── plot_select_from_model_diabetes.py
│   ├── gaussian_process/
│   │   ├── README.txt
│   │   ├── plot_compare_gpr_krr.py
│   │   ├── plot_gpc.py
│   │   ├── plot_gpc_iris.py
│   │   ├── plot_gpc_isoprobability.py
│   │   ├── plot_gpc_xor.py
│   │   ├── plot_gpr_co2.py
│   │   ├── plot_gpr_noisy.py
│   │   ├── plot_gpr_noisy_targets.py
│   │   ├── plot_gpr_on_structured_data.py
│   │   └── plot_gpr_prior_posterior.py
│   ├── impute/
│   │   ├── README.txt
│   │   ├── plot_iterative_imputer_variants_comparison.py
│   │   └── plot_missing_values.py
│   ├── inspection/
│   │   ├── README.txt
│   │   ├── plot_linear_model_coefficient_interpretation.py
│   │   ├── plot_partial_dependence.py
│   │   ├── plot_permutation_importance.py
│   │   └── plot_permutation_importance_multicollinear.py
│   ├── kernel_approximation/
│   │   ├── README.txt
│   │   └── plot_scalable_poly_kernels.py
│   ├── linear_model/
│   │   ├── README.txt
│   │   ├── plot_ard.py
│   │   ├── plot_bayesian_ridge.py
│   │   ├── plot_bayesian_ridge_curvefit.py
│   │   ├── plot_elastic_net_precomputed_gram_matrix_with_weighted_samples.py
│   │   ├── plot_huber_vs_ridge.py
│   │   ├── plot_iris_logistic.py
│   │   ├── plot_lasso_and_elasticnet.py
│   │   ├── plot_lasso_coordinate_descent_path.py
│   │   ├── plot_lasso_dense_vs_sparse_data.py
│   │   ├── plot_lasso_lars.py
│   │   ├── plot_lasso_model_selection.py
│   │   ├── plot_logistic.py
│   │   ├── plot_logistic_l1_l2_sparsity.py
│   │   ├── plot_logistic_multinomial.py
│   │   ├── plot_logistic_path.py
│   │   ├── plot_multi_task_lasso_support.py
│   │   ├── plot_nnls.py
│   │   ├── plot_ols.py
│   │   ├── plot_ols_3d.py
│   │   ├── plot_ols_ridge_variance.py
│   │   ├── plot_omp.py
│   │   ├── plot_poisson_regression_non_normal_loss.py
│   │   ├── plot_polynomial_interpolation.py
│   │   ├── plot_quantile_regression.py
│   │   ├── plot_ransac.py
│   │   ├── plot_ridge_coeffs.py
│   │   ├── plot_ridge_path.py
│   │   ├── plot_robust_fit.py
│   │   ├── plot_sgd_comparison.py
│   │   ├── plot_sgd_early_stopping.py
│   │   ├── plot_sgd_iris.py
│   │   ├── plot_sgd_loss_functions.py
│   │   ├── plot_sgd_penalties.py
│   │   ├── plot_sgd_separating_hyperplane.py
│   │   ├── plot_sgd_weighted_samples.py
│   │   ├── plot_sgdocsvm_vs_ocsvm.py
│   │   ├── plot_sparse_logistic_regression_20newsgroups.py
│   │   ├── plot_sparse_logistic_regression_mnist.py
│   │   ├── plot_theilsen.py
│   │   └── plot_tweedie_regression_insurance_claims.py
│   ├── manifold/
│   │   ├── README.txt
│   │   ├── plot_compare_methods.py
│   │   ├── plot_lle_digits.py
│   │   ├── plot_manifold_sphere.py
│   │   ├── plot_mds.py
│   │   ├── plot_swissroll.py
│   │   └── plot_t_sne_perplexity.py
│   ├── miscellaneous/
│   │   ├── README.txt
│   │   ├── plot_anomaly_comparison.py
│   │   ├── plot_changed_only_pprint_parameter.py
│   │   ├── plot_display_object_visualization.py
│   │   ├── plot_isotonic_regression.py
│   │   ├── plot_johnson_lindenstrauss_bound.py
│   │   ├── plot_kernel_approximation.py
│   │   ├── plot_kernel_ridge_regression.py
│   │   ├── plot_multilabel.py
│   │   ├── plot_multioutput_face_completion.py
│   │   ├── plot_partial_dependence_visualization_api.py
│   │   ├── plot_pipeline_display.py
│   │   └── plot_roc_curve_visualization_api.py
│   ├── mixture/
│   │   ├── README.txt
│   │   ├── plot_concentration_prior.py
│   │   ├── plot_gmm.py
│   │   ├── plot_gmm_covariances.py
│   │   ├── plot_gmm_pdf.py
│   │   ├── plot_gmm_selection.py
│   │   └── plot_gmm_sin.py
│   ├── model_selection/
│   │   ├── README.txt
│   │   ├── grid_search_text_feature_extraction.py
│   │   ├── plot_confusion_matrix.py
│   │   ├── plot_cv_indices.py
│   │   ├── plot_cv_predict.py
│   │   ├── plot_det.py
│   │   ├── plot_grid_search_digits.py
│   │   ├── plot_grid_search_refit_callable.py
│   │   ├── plot_grid_search_stats.py
│   │   ├── plot_learning_curve.py
│   │   ├── plot_multi_metric_evaluation.py
│   │   ├── plot_nested_cross_validation_iris.py
│   │   ├── plot_permutation_tests_for_classification.py
│   │   ├── plot_precision_recall.py
│   │   ├── plot_randomized_search.py
│   │   ├── plot_roc.py
│   │   ├── plot_roc_crossval.py
│   │   ├── plot_successive_halving_heatmap.py
│   │   ├── plot_successive_halving_iterations.py
│   │   ├── plot_train_error_vs_test_error.py
│   │   ├── plot_underfitting_overfitting.py
│   │   └── plot_validation_curve.py
│   ├── multioutput/
│   │   ├── README.txt
│   │   └── plot_classifier_chain_yeast.py
│   ├── neighbors/
│   │   ├── README.txt
│   │   ├── approximate_nearest_neighbors.py
│   │   ├── plot_caching_nearest_neighbors.py
│   │   ├── plot_classification.py
│   │   ├── plot_digits_kde_sampling.py
│   │   ├── plot_kde_1d.py
│   │   ├── plot_lof_novelty_detection.py
│   │   ├── plot_lof_outlier_detection.py
│   │   ├── plot_nca_classification.py
│   │   ├── plot_nca_dim_reduction.py
│   │   ├── plot_nca_illustration.py
│   │   ├── plot_nearest_centroid.py
│   │   ├── plot_regression.py
│   │   └── plot_species_kde.py
│   ├── neural_networks/
│   │   ├── README.txt
│   │   ├── plot_mlp_alpha.py
│   │   ├── plot_mlp_training_curves.py
│   │   ├── plot_mnist_filters.py
│   │   └── plot_rbm_logistic_classification.py
│   ├── preprocessing/
│   │   ├── README.txt
│   │   ├── plot_all_scaling.py
│   │   ├── plot_discretization.py
│   │   ├── plot_discretization_classification.py
│   │   ├── plot_discretization_strategies.py
│   │   ├── plot_map_data_to_normal.py
│   │   └── plot_scaling_importance.py
│   ├── release_highlights/
│   │   ├── README.txt
│   │   ├── plot_release_highlights_0_22_0.py
│   │   ├── plot_release_highlights_0_23_0.py
│   │   ├── plot_release_highlights_0_24_0.py
│   │   └── plot_release_highlights_1_0_0.py
│   ├── semi_supervised/
│   │   ├── README.txt
│   │   ├── plot_label_propagation_digits.py
│   │   ├── plot_label_propagation_digits_active_learning.py
│   │   ├── plot_label_propagation_structure.py
│   │   ├── plot_self_training_varying_threshold.py
│   │   ├── plot_semi_supervised_newsgroups.py
│   │   └── plot_semi_supervised_versus_svm_iris.py
│   ├── svm/
│   │   ├── README.txt
│   │   ├── plot_custom_kernel.py
│   │   ├── plot_iris_svc.py
│   │   ├── plot_linearsvc_support_vectors.py
│   │   ├── plot_oneclass.py
│   │   ├── plot_rbf_parameters.py
│   │   ├── plot_separating_hyperplane.py
│   │   ├── plot_separating_hyperplane_unbalanced.py
│   │   ├── plot_svm_anova.py
│   │   ├── plot_svm_kernels.py
│   │   ├── plot_svm_margin.py
│   │   ├── plot_svm_nonlinear.py
│   │   ├── plot_svm_regression.py
│   │   ├── plot_svm_scale_c.py
│   │   ├── plot_svm_tie_breaking.py
│   │   └── plot_weighted_samples.py
│   ├── text/
│   │   ├── README.txt
│   │   ├── plot_document_classification_20newsgroups.py
│   │   ├── plot_document_clustering.py
│   │   └── plot_hashing_vs_dict_vectorizer.py
│   └── tree/
│       ├── README.txt
│       ├── plot_cost_complexity_pruning.py
│       ├── plot_iris_dtc.py
│       ├── plot_tree_regression.py
│       ├── plot_tree_regression_multioutput.py
│       └── plot_unveil_tree_structure.py
├── lgtm.yml
├── maint_tools/
│   ├── check_pxd_in_installation.py
│   ├── create_issue_from_juint.py
│   ├── sort_whats_new.py
│   ├── test_docstrings.py
│   └── whats_missing.sh
├── pyproject.toml
├── setup.cfg
├── setup.py
└── sklearn/
    ├── __check_build/
    │   ├── __init__.py
    │   ├── _check_build.pyx
    │   └── setup.py
    ├── __init__.py
    ├── _build_utils/
    │   ├── __init__.py
    │   ├── openmp_helpers.py
    │   └── pre_build_helpers.py
    ├── _config.py
    ├── _distributor_init.py
    ├── _isotonic.pyx
    ├── _loss/
    │   ├── __init__.py
    │   ├── glm_distribution.py
    │   └── tests/
    │       ├── __init__.py
    │       └── test_glm_distribution.py
    ├── _min_dependencies.py
    ├── base.py
    ├── calibration.py
    ├── cluster/
    │   ├── __init__.py
    │   ├── _affinity_propagation.py
    │   ├── _agglomerative.py
    │   ├── _bicluster.py
    │   ├── _birch.py
    │   ├── _dbscan.py
    │   ├── _dbscan_inner.pyx
    │   ├── _feature_agglomeration.py
    │   ├── _hierarchical_fast.pyx
    │   ├── _k_means_common.pxd
    │   ├── _k_means_common.pyx
    │   ├── _k_means_elkan.pyx
    │   ├── _k_means_lloyd.pyx
    │   ├── _k_means_minibatch.pyx
    │   ├── _kmeans.py
    │   ├── _mean_shift.py
    │   ├── _optics.py
    │   ├── _spectral.py
    │   ├── setup.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── common.py
    │       ├── test_affinity_propagation.py
    │       ├── test_bicluster.py
    │       ├── test_birch.py
    │       ├── test_dbscan.py
    │       ├── test_feature_agglomeration.py
    │       ├── test_hierarchical.py
    │       ├── test_k_means.py
    │       ├── test_mean_shift.py
    │       ├── test_optics.py
    │       └── test_spectral.py
    ├── compose/
    │   ├── __init__.py
    │   ├── _column_transformer.py
    │   ├── _target.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_column_transformer.py
    │       └── test_target.py
    ├── conftest.py
    ├── covariance/
    │   ├── __init__.py
    │   ├── _elliptic_envelope.py
    │   ├── _empirical_covariance.py
    │   ├── _graph_lasso.py
    │   ├── _robust_covariance.py
    │   ├── _shrunk_covariance.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_covariance.py
    │       ├── test_elliptic_envelope.py
    │       ├── test_graphical_lasso.py
    │       └── test_robust_covariance.py
    ├── cross_decomposition/
    │   ├── __init__.py
    │   ├── _pls.py
    │   └── tests/
    │       ├── __init__.py
    │       └── test_pls.py
    ├── datasets/
    │   ├── __init__.py
    │   ├── _base.py
    │   ├── _california_housing.py
    │   ├── _covtype.py
    │   ├── _kddcup99.py
    │   ├── _lfw.py
    │   ├── _olivetti_faces.py
    │   ├── _openml.py
    │   ├── _rcv1.py
    │   ├── _samples_generator.py
    │   ├── _species_distributions.py
    │   ├── _svmlight_format_fast.pyx
    │   ├── _svmlight_format_io.py
    │   ├── _twenty_newsgroups.py
    │   ├── data/
    │   │   ├── __init__.py
    │   │   ├── boston_house_prices.csv
    │   │   ├── breast_cancer.csv
    │   │   ├── iris.csv
    │   │   ├── linnerud_exercise.csv
    │   │   ├── linnerud_physiological.csv
    │   │   └── wine_data.csv
    │   ├── descr/
    │   │   ├── __init__.py
    │   │   ├── boston_house_prices.rst
    │   │   ├── breast_cancer.rst
    │   │   ├── california_housing.rst
    │   │   ├── covtype.rst
    │   │   ├── diabetes.rst
    │   │   ├── digits.rst
    │   │   ├── iris.rst
    │   │   ├── kddcup99.rst
    │   │   ├── lfw.rst
    │   │   ├── linnerud.rst
    │   │   ├── olivetti_faces.rst
    │   │   ├── rcv1.rst
    │   │   ├── twenty_newsgroups.rst
    │   │   └── wine_data.rst
    │   ├── images/
    │   │   ├── README.txt
    │   │   └── __init__.py
    │   ├── setup.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── conftest.py
    │       ├── data/
    │       │   ├── __init__.py
    │       │   ├── openml/
    │       │   │   ├── __init__.py
    │       │   │   ├── id_1/
    │       │   │   │   └── __init__.py
    │       │   │   ├── id_1119/
    │       │   │   │   └── __init__.py
    │       │   │   ├── id_2/
    │       │   │   │   └── __init__.py
    │       │   │   ├── id_292/
    │       │   │   │   └── __init__.py
    │       │   │   ├── id_3/
    │       │   │   │   └── __init__.py
    │       │   │   ├── id_40589/
    │       │   │   │   └── __init__.py
    │       │   │   ├── id_40675/
    │       │   │   │   └── __init__.py
    │       │   │   ├── id_40945/
    │       │   │   │   └── __init__.py
    │       │   │   ├── id_40966/
    │       │   │   │   └── __init__.py
    │       │   │   ├── id_42585/
    │       │   │   │   └── __init__.py
    │       │   │   ├── id_561/
    │       │   │   │   └── __init__.py
    │       │   │   ├── id_61/
    │       │   │   │   └── __init__.py
    │       │   │   └── id_62/
    │       │   │       └── __init__.py
    │       │   ├── svmlight_classification.txt
    │       │   ├── svmlight_invalid.txt
    │       │   ├── svmlight_invalid_order.txt
    │       │   └── svmlight_multilabel.txt
    │       ├── test_20news.py
    │       ├── test_base.py
    │       ├── test_california_housing.py
    │       ├── test_common.py
    │       ├── test_covtype.py
    │       ├── test_kddcup99.py
    │       ├── test_lfw.py
    │       ├── test_olivetti_faces.py
    │       ├── test_openml.py
    │       ├── test_rcv1.py
    │       ├── test_samples_generator.py
    │       └── test_svmlight_format.py
    ├── decomposition/
    │   ├── __init__.py
    │   ├── _base.py
    │   ├── _cdnmf_fast.pyx
    │   ├── _dict_learning.py
    │   ├── _factor_analysis.py
    │   ├── _fastica.py
    │   ├── _incremental_pca.py
    │   ├── _kernel_pca.py
    │   ├── _lda.py
    │   ├── _nmf.py
    │   ├── _online_lda_fast.pyx
    │   ├── _pca.py
    │   ├── _sparse_pca.py
    │   ├── _truncated_svd.py
    │   ├── setup.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_dict_learning.py
    │       ├── test_factor_analysis.py
    │       ├── test_fastica.py
    │       ├── test_incremental_pca.py
    │       ├── test_kernel_pca.py
    │       ├── test_nmf.py
    │       ├── test_online_lda.py
    │       ├── test_pca.py
    │       ├── test_sparse_pca.py
    │       └── test_truncated_svd.py
    ├── discriminant_analysis.py
    ├── dummy.py
    ├── ensemble/
    │   ├── __init__.py
    │   ├── _bagging.py
    │   ├── _base.py
    │   ├── _forest.py
    │   ├── _gb.py
    │   ├── _gb_losses.py
    │   ├── _gradient_boosting.pyx
    │   ├── _hist_gradient_boosting/
    │   │   ├── __init__.py
    │   │   ├── _binning.pyx
    │   │   ├── _bitset.pxd
    │   │   ├── _bitset.pyx
    │   │   ├── _gradient_boosting.pyx
    │   │   ├── _loss.pyx
    │   │   ├── _predictor.pyx
    │   │   ├── binning.py
    │   │   ├── common.pxd
    │   │   ├── common.pyx
    │   │   ├── gradient_boosting.py
    │   │   ├── grower.py
    │   │   ├── histogram.pyx
    │   │   ├── loss.py
    │   │   ├── predictor.py
    │   │   ├── splitting.pyx
    │   │   ├── tests/
    │   │   │   ├── __init__.py
    │   │   │   ├── test_binning.py
    │   │   │   ├── test_bitset.py
    │   │   │   ├── test_compare_lightgbm.py
    │   │   │   ├── test_gradient_boosting.py
    │   │   │   ├── test_grower.py
    │   │   │   ├── test_histogram.py
    │   │   │   ├── test_loss.py
    │   │   │   ├── test_monotonic_contraints.py
    │   │   │   ├── test_predictor.py
    │   │   │   ├── test_splitting.py
    │   │   │   └── test_warm_start.py
    │   │   └── utils.pyx
    │   ├── _iforest.py
    │   ├── _stacking.py
    │   ├── _voting.py
    │   ├── _weight_boosting.py
    │   ├── setup.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_bagging.py
    │       ├── test_base.py
    │       ├── test_common.py
    │       ├── test_forest.py
    │       ├── test_gradient_boosting.py
    │       ├── test_gradient_boosting_loss_functions.py
    │       ├── test_iforest.py
    │       ├── test_stacking.py
    │       ├── test_voting.py
    │       └── test_weight_boosting.py
    ├── exceptions.py
    ├── experimental/
    │   ├── __init__.py
    │   ├── enable_halving_search_cv.py
    │   ├── enable_hist_gradient_boosting.py
    │   ├── enable_iterative_imputer.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_enable_hist_gradient_boosting.py
    │       ├── test_enable_iterative_imputer.py
    │       └── test_enable_successive_halving.py
    ├── externals/
    │   ├── README
    │   ├── __init__.py
    │   ├── _arff.py
    │   ├── _lobpcg.py
    │   ├── _packaging/
    │   │   ├── __init__.py
    │   │   ├── _structures.py
    │   │   └── version.py
    │   ├── _pilutil.py
    │   └── conftest.py
    ├── feature_extraction/
    │   ├── __init__.py
    │   ├── _dict_vectorizer.py
    │   ├── _hash.py
    │   ├── _hashing_fast.pyx
    │   ├── _stop_words.py
    │   ├── image.py
    │   ├── setup.py
    │   ├── tests/
    │   │   ├── __init__.py
    │   │   ├── test_dict_vectorizer.py
    │   │   ├── test_feature_hasher.py
    │   │   ├── test_image.py
    │   │   └── test_text.py
    │   └── text.py
    ├── feature_selection/
    │   ├── __init__.py
    │   ├── _base.py
    │   ├── _from_model.py
    │   ├── _mutual_info.py
    │   ├── _rfe.py
    │   ├── _sequential.py
    │   ├── _univariate_selection.py
    │   ├── _variance_threshold.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_base.py
    │       ├── test_chi2.py
    │       ├── test_feature_select.py
    │       ├── test_from_model.py
    │       ├── test_mutual_info.py
    │       ├── test_rfe.py
    │       ├── test_sequential.py
    │       └── test_variance_threshold.py
    ├── gaussian_process/
    │   ├── __init__.py
    │   ├── _gpc.py
    │   ├── _gpr.py
    │   ├── kernels.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── _mini_sequence_kernel.py
    │       ├── test_gpc.py
    │       ├── test_gpr.py
    │       └── test_kernels.py
    ├── impute/
    │   ├── __init__.py
    │   ├── _base.py
    │   ├── _iterative.py
    │   ├── _knn.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_base.py
    │       ├── test_common.py
    │       ├── test_impute.py
    │       └── test_knn.py
    ├── inspection/
    │   ├── __init__.py
    │   ├── _partial_dependence.py
    │   ├── _permutation_importance.py
    │   ├── _plot/
    │   │   ├── __init__.py
    │   │   ├── partial_dependence.py
    │   │   └── tests/
    │   │       ├── __init__.py
    │   │       └── test_plot_partial_dependence.py
    │   ├── setup.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_partial_dependence.py
    │       └── test_permutation_importance.py
    ├── isotonic.py
    ├── kernel_approximation.py
    ├── kernel_ridge.py
    ├── linear_model/
    │   ├── __init__.py
    │   ├── _base.py
    │   ├── _bayes.py
    │   ├── _cd_fast.pyx
    │   ├── _coordinate_descent.py
    │   ├── _glm/
    │   │   ├── __init__.py
    │   │   ├── glm.py
    │   │   ├── link.py
    │   │   └── tests/
    │   │       ├── __init__.py
    │   │       ├── test_glm.py
    │   │       └── test_link.py
    │   ├── _huber.py
    │   ├── _least_angle.py
    │   ├── _logistic.py
    │   ├── _omp.py
    │   ├── _passive_aggressive.py
    │   ├── _perceptron.py
    │   ├── _quantile.py
    │   ├── _ransac.py
    │   ├── _ridge.py
    │   ├── _sag.py
    │   ├── _sag_fast.pyx.tp
    │   ├── _sgd_fast.pxd
    │   ├── _sgd_fast.pyx
    │   ├── _sgd_fast_helpers.h
    │   ├── _stochastic_gradient.py
    │   ├── _theil_sen.py
    │   ├── setup.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_base.py
    │       ├── test_bayes.py
    │       ├── test_common.py
    │       ├── test_coordinate_descent.py
    │       ├── test_huber.py
    │       ├── test_least_angle.py
    │       ├── test_logistic.py
    │       ├── test_omp.py
    │       ├── test_passive_aggressive.py
    │       ├── test_perceptron.py
    │       ├── test_quantile.py
    │       ├── test_ransac.py
    │       ├── test_ridge.py
    │       ├── test_sag.py
    │       ├── test_sgd.py
    │       ├── test_sparse_coordinate_descent.py
    │       └── test_theil_sen.py
    ├── manifold/
    │   ├── __init__.py
    │   ├── _barnes_hut_tsne.pyx
    │   ├── _isomap.py
    │   ├── _locally_linear.py
    │   ├── _mds.py
    │   ├── _spectral_embedding.py
    │   ├── _t_sne.py
    │   ├── _utils.pyx
    │   ├── setup.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_isomap.py
    │       ├── test_locally_linear.py
    │       ├── test_mds.py
    │       ├── test_spectral_embedding.py
    │       └── test_t_sne.py
    ├── metrics/
    │   ├── __init__.py
    │   ├── _base.py
    │   ├── _classification.py
    │   ├── _dist_metrics.pxd
    │   ├── _dist_metrics.pyx
    │   ├── _pairwise_fast.pyx
    │   ├── _plot/
    │   │   ├── __init__.py
    │   │   ├── base.py
    │   │   ├── confusion_matrix.py
    │   │   ├── det_curve.py
    │   │   ├── precision_recall_curve.py
    │   │   ├── roc_curve.py
    │   │   └── tests/
    │   │       ├── __init__.py
    │   │       ├── test_base.py
    │   │       ├── test_common_curve_display.py
    │   │       ├── test_confusion_matrix_display.py
    │   │       ├── test_det_curve_display.py
    │   │       ├── test_plot_confusion_matrix.py
    │   │       ├── test_plot_curve_common.py
    │   │       ├── test_plot_det_curve.py
    │   │       ├── test_plot_precision_recall.py
    │   │       ├── test_plot_roc_curve.py
    │   │       ├── test_precision_recall_display.py
    │   │       └── test_roc_curve_display.py
    │   ├── _ranking.py
    │   ├── _regression.py
    │   ├── _scorer.py
    │   ├── cluster/
    │   │   ├── __init__.py
    │   │   ├── _bicluster.py
    │   │   ├── _expected_mutual_info_fast.pyx
    │   │   ├── _supervised.py
    │   │   ├── _unsupervised.py
    │   │   ├── setup.py
    │   │   └── tests/
    │   │       ├── __init__.py
    │   │       ├── test_bicluster.py
    │   │       ├── test_common.py
    │   │       ├── test_supervised.py
    │   │       └── test_unsupervised.py
    │   ├── pairwise.py
    │   ├── setup.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_classification.py
    │       ├── test_common.py
    │       ├── test_dist_metrics.py
    │       ├── test_pairwise.py
    │       ├── test_ranking.py
    │       ├── test_regression.py
    │       └── test_score_objects.py
    ├── mixture/
    │   ├── __init__.py
    │   ├── _base.py
    │   ├── _bayesian_mixture.py
    │   ├── _gaussian_mixture.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_bayesian_mixture.py
    │       ├── test_gaussian_mixture.py
    │       └── test_mixture.py
    ├── model_selection/
    │   ├── __init__.py
    │   ├── _search.py
    │   ├── _search_successive_halving.py
    │   ├── _split.py
    │   ├── _validation.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── common.py
    │       ├── test_search.py
    │       ├── test_split.py
    │       ├── test_successive_halving.py
    │       └── test_validation.py
    ├── multiclass.py
    ├── multioutput.py
    ├── naive_bayes.py
    ├── neighbors/
    │   ├── __init__.py
    │   ├── _ball_tree.pyx
    │   ├── _base.py
    │   ├── _binary_tree.pxi
    │   ├── _classification.py
    │   ├── _distance_metric.py
    │   ├── _graph.py
    │   ├── _kd_tree.pyx
    │   ├── _kde.py
    │   ├── _lof.py
    │   ├── _nca.py
    │   ├── _nearest_centroid.py
    │   ├── _partition_nodes.pxd
    │   ├── _partition_nodes.pyx
    │   ├── _quad_tree.pxd
    │   ├── _quad_tree.pyx
    │   ├── _regression.py
    │   ├── _unsupervised.py
    │   ├── setup.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_ball_tree.py
    │       ├── test_graph.py
    │       ├── test_kd_tree.py
    │       ├── test_kde.py
    │       ├── test_lof.py
    │       ├── test_nca.py
    │       ├── test_nearest_centroid.py
    │       ├── test_neighbors.py
    │       ├── test_neighbors_pipeline.py
    │       ├── test_neighbors_tree.py
    │       └── test_quad_tree.py
    ├── neural_network/
    │   ├── __init__.py
    │   ├── _base.py
    │   ├── _multilayer_perceptron.py
    │   ├── _rbm.py
    │   ├── _stochastic_optimizers.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_base.py
    │       ├── test_mlp.py
    │       ├── test_rbm.py
    │       └── test_stochastic_optimizers.py
    ├── pipeline.py
    ├── preprocessing/
    │   ├── __init__.py
    │   ├── _csr_polynomial_expansion.pyx
    │   ├── _data.py
    │   ├── _discretization.py
    │   ├── _encoders.py
    │   ├── _function_transformer.py
    │   ├── _label.py
    │   ├── _polynomial.py
    │   ├── setup.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_common.py
    │       ├── test_data.py
    │       ├── test_discretization.py
    │       ├── test_encoders.py
    │       ├── test_function_transformer.py
    │       ├── test_label.py
    │       └── test_polynomial.py
    ├── random_projection.py
    ├── semi_supervised/
    │   ├── __init__.py
    │   ├── _label_propagation.py
    │   ├── _self_training.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_label_propagation.py
    │       └── test_self_training.py
    ├── setup.py
    ├── svm/
    │   ├── __init__.py
    │   ├── _base.py
    │   ├── _bounds.py
    │   ├── _classes.py
    │   ├── _liblinear.pxi
    │   ├── _liblinear.pyx
    │   ├── _libsvm.pxi
    │   ├── _libsvm.pyx
    │   ├── _libsvm_sparse.pyx
    │   ├── _newrand.pyx
    │   ├── setup.py
    │   ├── src/
    │   │   ├── liblinear/
    │   │   │   ├── COPYRIGHT
    │   │   │   ├── _cython_blas_helpers.h
    │   │   │   ├── liblinear_helper.c
    │   │   │   ├── linear.cpp
    │   │   │   ├── linear.h
    │   │   │   ├── tron.cpp
    │   │   │   └── tron.h
    │   │   ├── libsvm/
    │   │   │   ├── LIBSVM_CHANGES
    │   │   │   ├── _svm_cython_blas_helpers.h
    │   │   │   ├── libsvm_helper.c
    │   │   │   ├── libsvm_sparse_helper.c
    │   │   │   ├── libsvm_template.cpp
    │   │   │   ├── svm.cpp
    │   │   │   └── svm.h
    │   │   └── newrand/
    │   │       └── newrand.h
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_bounds.py
    │       ├── test_sparse.py
    │       └── test_svm.py
    ├── tests/
    │   ├── __init__.py
    │   ├── test_base.py
    │   ├── test_build.py
    │   ├── test_calibration.py
    │   ├── test_check_build.py
    │   ├── test_common.py
    │   ├── test_config.py
    │   ├── test_discriminant_analysis.py
    │   ├── test_docstring_parameters.py
    │   ├── test_dummy.py
    │   ├── test_init.py
    │   ├── test_isotonic.py
    │   ├── test_kernel_approximation.py
    │   ├── test_kernel_ridge.py
    │   ├── test_metaestimators.py
    │   ├── test_min_dependencies_readme.py
    │   ├── test_multiclass.py
    │   ├── test_multioutput.py
    │   ├── test_naive_bayes.py
    │   ├── test_pipeline.py
    │   └── test_random_projection.py
    ├── tree/
    │   ├── __init__.py
    │   ├── _classes.py
    │   ├── _criterion.pxd
    │   ├── _criterion.pyx
    │   ├── _export.py
    │   ├── _reingold_tilford.py
    │   ├── _splitter.pxd
    │   ├── _splitter.pyx
    │   ├── _tree.pxd
    │   ├── _tree.pyx
    │   ├── _utils.pxd
    │   ├── _utils.pyx
    │   ├── setup.py
    │   └── tests/
    │       ├── __init__.py
    │       ├── test_export.py
    │       ├── test_reingold_tilford.py
    │       └── test_tree.py
    └── utils/
        ├── __init__.py
        ├── _arpack.py
        ├── _cython_blas.pxd
        ├── _cython_blas.pyx
        ├── _encode.py
        ├── _estimator_html_repr.py
        ├── _fast_dict.pxd
        ├── _fast_dict.pyx
        ├── _joblib.py
        ├── _logistic_sigmoid.pyx
        ├── _mask.py
        ├── _mocking.py
        ├── _openmp_helpers.pyx
        ├── _pprint.py
        ├── _random.pxd
        ├── _random.pyx
        ├── _readonly_array_wrapper.pyx
        ├── _seq_dataset.pxd.tp
        ├── _seq_dataset.pyx.tp
        ├── _show_versions.py
        ├── _tags.py
        ├── _testing.py
        ├── _typedefs.pxd
        ├── _typedefs.pyx
        ├── _weight_vector.pxd.tp
        ├── _weight_vector.pyx.tp
        ├── arrayfuncs.pyx
        ├── class_weight.py
        ├── deprecation.py
        ├── estimator_checks.py
        ├── extmath.py
        ├── fixes.py
        ├── graph.py
        ├── metaestimators.py
        ├── multiclass.py
        ├── murmurhash.pxd
        ├── murmurhash.pyx
        ├── optimize.py
        ├── random.py
        ├── setup.py
        ├── sparsefuncs.py
        ├── sparsefuncs_fast.pyx
        ├── src/
        │   ├── MurmurHash3.cpp
        │   └── MurmurHash3.h
        ├── stats.py
        ├── tests/
        │   ├── __init__.py
        │   ├── conftest.py
        │   ├── test_arpack.py
        │   ├── test_arrayfuncs.py
        │   ├── test_class_weight.py
        │   ├── test_cython_blas.py
        │   ├── test_cython_templating.py
        │   ├── test_deprecation.py
        │   ├── test_encode.py
        │   ├── test_estimator_checks.py
        │   ├── test_estimator_html_repr.py
        │   ├── test_extmath.py
        │   ├── test_fast_dict.py
        │   ├── test_fixes.py
        │   ├── test_graph.py
        │   ├── test_metaestimators.py
        │   ├── test_mocking.py
        │   ├── test_multiclass.py
        │   ├── test_murmurhash.py
        │   ├── test_optimize.py
        │   ├── test_parallel.py
        │   ├── test_pprint.py
        │   ├── test_random.py
        │   ├── test_readonly_wrapper.py
        │   ├── test_seq_dataset.py
        │   ├── test_shortest_path.py
        │   ├── test_show_versions.py
        │   ├── test_sparsefuncs.py
        │   ├── test_stats.py
        │   ├── test_tags.py
        │   ├── test_testing.py
        │   ├── test_utils.py
        │   ├── test_validation.py
        │   └── test_weight_vector.py
        └── validation.py

SYMBOL INDEX (9625 symbols across 598 files)

FILE: asv_benchmarks/benchmarks/cluster.py
  class KMeansBenchmark (line 8) | class KMeansBenchmark(Predictor, Transformer, Estimator, Benchmark):
    method setup_cache (line 16) | def setup_cache(self):
    method make_data (line 19) | def make_data(self, params):
    method make_estimator (line 29) | def make_estimator(self, params):
    method make_scorers (line 46) | def make_scorers(self):
  class MiniBatchKMeansBenchmark (line 57) | class MiniBatchKMeansBenchmark(Predictor, Transformer, Estimator, Benchm...
    method setup_cache (line 65) | def setup_cache(self):
    method make_data (line 68) | def make_data(self, params):
    method make_estimator (line 78) | def make_estimator(self, params):
    method make_scorers (line 96) | def make_scorers(self):

FILE: asv_benchmarks/benchmarks/common.py
  function get_from_config (line 13) | def get_from_config():
  function get_estimator_path (line 59) | def get_estimator_path(benchmark, directory, params, save=False):
  function clear_tmp (line 74) | def clear_tmp():
  class Benchmark (line 81) | class Benchmark(ABC):
    method params (line 116) | def params(self):
  class Estimator (line 120) | class Estimator(ABC):
    method make_data (line 124) | def make_data(self, params):
    method make_estimator (line 131) | def make_estimator(self, params):
    method skip (line 135) | def skip(self, params):
    method setup_cache (line 139) | def setup_cache(self):
    method setup (line 162) | def setup(self, *params):
    method time_fit (line 180) | def time_fit(self, *args):
    method peakmem_fit (line 183) | def peakmem_fit(self, *args):
    method track_train_score (line 186) | def track_train_score(self, *args):
    method track_test_score (line 193) | def track_test_score(self, *args):
  class Predictor (line 201) | class Predictor(ABC):
    method time_predict (line 206) | def time_predict(self, *args):
    method peakmem_predict (line 209) | def peakmem_predict(self, *args):
    method track_same_prediction (line 214) | def track_same_prediction(self, *args):
    method params (line 226) | def params(self):
  class Transformer (line 230) | class Transformer(ABC):
    method time_transform (line 235) | def time_transform(self, *args):
    method peakmem_transform (line 238) | def peakmem_transform(self, *args):
    method track_same_transform (line 243) | def track_same_transform(self, *args):
    method params (line 255) | def params(self):

FILE: asv_benchmarks/benchmarks/datasets.py
  function _blobs_dataset (line 25) | def _blobs_dataset(n_samples=500000, n_features=3, n_clusters=100, dtype...
  function _20newsgroups_highdim_dataset (line 36) | def _20newsgroups_highdim_dataset(n_samples=None, ngrams=(1, 1), dtype=n...
  function _20newsgroups_lowdim_dataset (line 47) | def _20newsgroups_lowdim_dataset(n_components=100, ngrams=(1, 1), dtype=...
  function _mnist_dataset (line 61) | def _mnist_dataset(dtype=np.float32):
  function _digits_dataset (line 71) | def _digits_dataset(n_samples=None, dtype=np.float32):
  function _synth_regression_dataset (line 83) | def _synth_regression_dataset(n_samples=100000, n_features=100, dtype=np...
  function _synth_regression_sparse_dataset (line 99) | def _synth_regression_sparse_dataset(
  function _synth_classification_dataset (line 117) | def _synth_classification_dataset(
  function _olivetti_faces_dataset (line 136) | def _olivetti_faces_dataset():
  function _random_dataset (line 150) | def _random_dataset(

FILE: asv_benchmarks/benchmarks/decomposition.py
  class PCABenchmark (line 8) | class PCABenchmark(Transformer, Estimator, Benchmark):
    method setup_cache (line 16) | def setup_cache(self):
    method make_data (line 19) | def make_data(self, params):
    method make_estimator (line 22) | def make_estimator(self, params):
    method make_scorers (line 29) | def make_scorers(self):
  class DictionaryLearningBenchmark (line 33) | class DictionaryLearningBenchmark(Transformer, Estimator, Benchmark):
    method setup_cache (line 41) | def setup_cache(self):
    method make_data (line 44) | def make_data(self, params):
    method make_estimator (line 47) | def make_estimator(self, params):
    method make_scorers (line 62) | def make_scorers(self):
  class MiniBatchDictionaryLearningBenchmark (line 66) | class MiniBatchDictionaryLearningBenchmark(Transformer, Estimator, Bench...
    method setup_cache (line 74) | def setup_cache(self):
    method make_data (line 77) | def make_data(self, params):
    method make_estimator (line 80) | def make_estimator(self, params):
    method make_scorers (line 94) | def make_scorers(self):

FILE: asv_benchmarks/benchmarks/ensemble.py
  class RandomForestClassifierBenchmark (line 16) | class RandomForestClassifierBenchmark(Predictor, Estimator, Benchmark):
    method setup_cache (line 24) | def setup_cache(self):
    method make_data (line 27) | def make_data(self, params):
    method make_estimator (line 37) | def make_estimator(self, params):
    method make_scorers (line 52) | def make_scorers(self):
  class GradientBoostingClassifierBenchmark (line 56) | class GradientBoostingClassifierBenchmark(Predictor, Estimator, Benchmark):
    method setup_cache (line 64) | def setup_cache(self):
    method make_data (line 67) | def make_data(self, params):
    method make_estimator (line 77) | def make_estimator(self, params):
    method make_scorers (line 91) | def make_scorers(self):
  class HistGradientBoostingClassifierBenchmark (line 95) | class HistGradientBoostingClassifierBenchmark(Predictor, Estimator, Benc...
    method setup_cache (line 103) | def setup_cache(self):
    method make_data (line 106) | def make_data(self, params):
    method make_estimator (line 113) | def make_estimator(self, params):
    method make_scorers (line 120) | def make_scorers(self):

FILE: asv_benchmarks/benchmarks/linear_model.py
  class LogisticRegressionBenchmark (line 20) | class LogisticRegressionBenchmark(Predictor, Estimator, Benchmark):
    method setup_cache (line 28) | def setup_cache(self):
    method make_data (line 31) | def make_data(self, params):
    method make_estimator (line 47) | def make_estimator(self, params):
    method make_scorers (line 63) | def make_scorers(self):
  class RidgeBenchmark (line 67) | class RidgeBenchmark(Predictor, Estimator, Benchmark):
    method setup_cache (line 78) | def setup_cache(self):
    method make_data (line 81) | def make_data(self, params):
    method make_estimator (line 93) | def make_estimator(self, params):
    method make_scorers (line 100) | def make_scorers(self):
    method skip (line 103) | def skip(self, params):
  class LinearRegressionBenchmark (line 111) | class LinearRegressionBenchmark(Predictor, Estimator, Benchmark):
    method setup_cache (line 119) | def setup_cache(self):
    method make_data (line 122) | def make_data(self, params):
    method make_estimator (line 134) | def make_estimator(self, params):
    method make_scorers (line 139) | def make_scorers(self):
  class SGDRegressorBenchmark (line 143) | class SGDRegressorBenchmark(Predictor, Estimator, Benchmark):
    method setup_cache (line 151) | def setup_cache(self):
    method make_data (line 154) | def make_data(self, params):
    method make_estimator (line 166) | def make_estimator(self, params):
    method make_scorers (line 171) | def make_scorers(self):
  class ElasticNetBenchmark (line 175) | class ElasticNetBenchmark(Predictor, Estimator, Benchmark):
    method setup_cache (line 183) | def setup_cache(self):
    method make_data (line 186) | def make_data(self, params):
    method make_estimator (line 198) | def make_estimator(self, params):
    method make_scorers (line 205) | def make_scorers(self):
    method skip (line 208) | def skip(self, params):
  class LassoBenchmark (line 216) | class LassoBenchmark(Predictor, Estimator, Benchmark):
    method setup_cache (line 224) | def setup_cache(self):
    method make_data (line 227) | def make_data(self, params):
    method make_estimator (line 239) | def make_estimator(self, params):
    method make_scorers (line 246) | def make_scorers(self):
    method skip (line 249) | def skip(self, params):

FILE: asv_benchmarks/benchmarks/manifold.py
  class TSNEBenchmark (line 7) | class TSNEBenchmark(Estimator, Benchmark):
    method setup_cache (line 15) | def setup_cache(self):
    method make_data (line 18) | def make_data(self, params):
    method make_estimator (line 25) | def make_estimator(self, params):
    method make_scorers (line 32) | def make_scorers(self):

FILE: asv_benchmarks/benchmarks/metrics.py
  class PairwiseDistancesBenchmark (line 7) | class PairwiseDistancesBenchmark(Benchmark):
    method setup (line 19) | def setup(self, *params):
    method time_pairwise_distances (line 41) | def time_pairwise_distances(self, *args):
    method peakmem_pairwise_distances (line 44) | def peakmem_pairwise_distances(self, *args):

FILE: asv_benchmarks/benchmarks/model_selection.py
  class CrossValidationBenchmark (line 9) | class CrossValidationBenchmark(Benchmark):
    method setup (line 19) | def setup(self, *params):
    method time_crossval (line 31) | def time_crossval(self, *args):
    method peakmem_crossval (line 34) | def peakmem_crossval(self, *args):
    method track_crossval (line 37) | def track_crossval(self, *args):
  class GridSearchBenchmark (line 41) | class GridSearchBenchmark(Predictor, Estimator, Benchmark):
    method setup_cache (line 51) | def setup_cache(self):
    method make_data (line 54) | def make_data(self, params):
    method make_estimator (line 59) | def make_estimator(self, params):
    method make_scorers (line 83) | def make_scorers(self):

FILE: asv_benchmarks/benchmarks/neighbors.py
  class KNeighborsClassifierBenchmark (line 8) | class KNeighborsClassifierBenchmark(Predictor, Estimator, Benchmark):
    method setup_cache (line 16) | def setup_cache(self):
    method make_data (line 19) | def make_data(self, params):
    method make_estimator (line 31) | def make_estimator(self, params):
    method make_scorers (line 38) | def make_scorers(self):

FILE: asv_benchmarks/benchmarks/svm.py
  class SVCBenchmark (line 8) | class SVCBenchmark(Predictor, Estimator, Benchmark):
    method setup_cache (line 14) | def setup_cache(self):
    method make_data (line 17) | def make_data(self, params):
    method make_estimator (line 20) | def make_estimator(self, params):
    method make_scorers (line 29) | def make_scorers(self):

FILE: asv_benchmarks/benchmarks/utils.py
  function neg_mean_inertia (line 6) | def neg_mean_inertia(X, labels, centers):
  function make_gen_classif_scorers (line 10) | def make_gen_classif_scorers(caller):
  function make_gen_reg_scorers (line 15) | def make_gen_reg_scorers(caller):
  function neg_mean_data_error (line 20) | def neg_mean_data_error(X, U, V):
  function make_dict_learning_scorers (line 24) | def make_dict_learning_scorers(caller):
  function explained_variance_ratio (line 39) | def explained_variance_ratio(Xt, X):
  function make_pca_scorers (line 43) | def make_pca_scorers(caller):

FILE: benchmarks/bench_covertype.py
  function load_data (line 72) | def load_data(dtype=np.float32, order="C", random_state=13):

FILE: benchmarks/bench_glmnet.py
  function rmse (line 28) | def rmse(a, b):
  function bench (line 32) | def bench(factory, X, Y, X_test, Y_test, ref_coef):

FILE: benchmarks/bench_hist_gradient_boosting.py
  function get_estimator_and_data (line 53) | def get_estimator_and_data():
  function one_run (line 92) | def one_run(n_samples):

FILE: benchmarks/bench_hist_gradient_boosting_adult.py
  function fit (line 28) | def fit(est, data_train, target_train, libname, **fit_params):
  function predict (line 36) | def predict(est, data_test, target_test):

FILE: benchmarks/bench_hist_gradient_boosting_categorical_only.py
  function fit (line 33) | def fit(est, data_train, target_train, libname, **fit_params):
  function predict (line 41) | def predict(est, data_test):

FILE: benchmarks/bench_hist_gradient_boosting_higgsboson.py
  function load_data (line 41) | def load_data():
  function fit (line 57) | def fit(est, data_train, target_train, libname):
  function predict (line 65) | def predict(est, data_test, target_test):

FILE: benchmarks/bench_hist_gradient_boosting_threading.py
  function get_estimator_and_data (line 69) | def get_estimator_and_data():
  function one_run (line 144) | def one_run(n_threads, n_samples):

FILE: benchmarks/bench_isolation_forest.py
  function print_outlier_ratio (line 32) | def print_outlier_ratio(y):

FILE: benchmarks/bench_isotonic.py
  function generate_perturbed_logarithm_dataset (line 22) | def generate_perturbed_logarithm_dataset(size):
  function generate_logistic_dataset (line 26) | def generate_logistic_dataset(size):
  function generate_pathological_dataset (line 31) | def generate_pathological_dataset(size):
  function bench_isotonic_regression (line 45) | def bench_isotonic_regression(Y):

FILE: benchmarks/bench_lasso.py
  function compute_bench (line 21) | def compute_bench(alpha, n_samples, n_features, precompute):

FILE: benchmarks/bench_mnist.py
  function load_data (line 60) | def load_data(dtype=np.float32, order="F"):

FILE: benchmarks/bench_multilabel_metrics.py
  function benchmark (line 43) | def benchmark(
  function _tabulate (line 106) | def _tabulate(results, metrics, formats):
  function _plot (line 120) | def _plot(

FILE: benchmarks/bench_online_ocsvm.py
  function print_outlier_ratio (line 41) | def print_outlier_ratio(y):
  function autolabel_auc (line 235) | def autolabel_auc(rects, ax):
  function autolabel_time (line 248) | def autolabel_time(rects, ax):

FILE: benchmarks/bench_plot_fastkmeans.py
  function compute_bench (line 10) | def compute_bench(samples_range, features_range):
  function compute_bench_2 (line 57) | def compute_bench_2(chunks):

FILE: benchmarks/bench_plot_hierarchical.py
  function compute_bench (line 10) | def compute_bench(samples_range, features_range):

FILE: benchmarks/bench_plot_incremental_pca.py
  function plot_results (line 19) | def plot_results(X, y, label):
  function benchmark (line 23) | def benchmark(estimator, data):
  function plot_feature_times (line 35) | def plot_feature_times(all_times, batch_size, all_components, data):
  function plot_feature_errors (line 50) | def plot_feature_errors(all_errors, batch_size, all_components, data):
  function plot_batch_times (line 64) | def plot_batch_times(all_times, n_features, all_batch_sizes, data):
  function plot_batch_errors (line 77) | def plot_batch_errors(all_errors, n_features, all_batch_sizes, data):
  function fixed_batch_size_comparison (line 90) | def fixed_batch_size_comparison(data):
  function variable_batch_size_comparison (line 113) | def variable_batch_size_comparison(data):

FILE: benchmarks/bench_plot_lasso_path.py
  function compute_bench (line 17) | def compute_bench(samples_range, features_range):

FILE: benchmarks/bench_plot_neighbors.py
  function get_data (line 13) | def get_data(N, D, dataset="dense"):
  function barplot_neighbors (line 26) | def barplot_neighbors(

FILE: benchmarks/bench_plot_nmf.py
  function _norm (line 42) | def _norm(x):
  function _nls_subproblem (line 49) | def _nls_subproblem(
  function _fit_projected_gradient (line 151) | def _fit_projected_gradient(X, W, H, tol, max_iter, nls_max_iter, alpha,...
  class _PGNMF (line 195) | class _PGNMF(NMF):
    method __init__ (line 203) | def __init__(
    method fit (line 227) | def fit(self, X, y=None, **params):
    method transform (line 231) | def transform(self, X):
    method inverse_transform (line 237) | def inverse_transform(self, W):
    method fit_transform (line 241) | def fit_transform(self, X, y=None, W=None, H=None):
    method _fit_transform (line 246) | def _fit_transform(self, X, y=None, W=None, H=None, update_H=True):
  function plot_results (line 323) | def plot_results(results_df, plot_name):
  function bench_one (line 359) | def bench_one(
  function run_bench (line 376) | def run_bench(X, clfs, plot_name, n_components, tol, alpha, l1_ratio):
  function load_20news (line 414) | def load_20news():
  function load_faces (line 427) | def load_faces():
  function build_clfs (line 436) | def build_clfs(cd_iters, pg_iters, mu_iters):

FILE: benchmarks/bench_plot_omp_lars.py
  function compute_bench (line 16) | def compute_bench(samples_range, features_range):

FILE: benchmarks/bench_plot_parallel_pairwise.py
  function plot (line 12) | def plot(func):
  function euclidean_distances (line 38) | def euclidean_distances(X, n_jobs):
  function rbf_kernels (line 42) | def rbf_kernels(X, n_jobs):

FILE: benchmarks/bench_plot_randomized_svd.py
  function unpickle (line 132) | def unpickle(file_name):
  function handle_missing_dataset (line 137) | def handle_missing_dataset(file_folder):
  function get_data (line 143) | def get_data(dataset_name):
  function plot_time_vs_s (line 197) | def plot_time_vs_s(time, norm, point_labels, title):
  function scatter_time_vs_s (line 221) | def scatter_time_vs_s(time, norm, point_labels, title):
  function plot_power_iter_vs_s (line 260) | def plot_power_iter_vs_s(power_iter, s, title):
  function svd_timing (line 270) | def svd_timing(
  function norm_diff (line 302) | def norm_diff(A, norm=2, msg=True, random_state=None):
  function scalable_frobenius_norm_discrepancy (line 324) | def scalable_frobenius_norm_discrepancy(X, U, s, V):
  function bench_a (line 340) | def bench_a(X, dataset_name, power_iter, n_oversamples, n_comps):
  function bench_b (line 396) | def bench_b(power_list):
  function bench_c (line 443) | def bench_c(datasets, n_comps):

FILE: benchmarks/bench_plot_svd.py
  function compute_bench (line 15) | def compute_bench(samples_range, features_range, n_iter=3, rank=50):

FILE: benchmarks/bench_random_projections.py
  function type_auto_or_float (line 26) | def type_auto_or_float(val):
  function type_auto_or_int (line 33) | def type_auto_or_int(val):
  function compute_time (line 40) | def compute_time(t_start, delta):
  function bench_scikit_transformer (line 46) | def bench_scikit_transformer(X, transformer):
  function make_sparse_random_data (line 70) | def make_sparse_random_data(n_samples, n_features, n_nonzeros, random_st...
  function print_row (line 85) | def print_row(clf_type, time_fit, time_transform):

FILE: benchmarks/bench_rcv1_logreg_convergence.py
  function get_loss (line 25) | def get_loss(w, intercept, myX, myy, C):
  function bench_one (line 38) | def bench_one(name, clf_type, clf_params, n_iter):
  function bench (line 67) | def bench(clfs):
  function plot_train_losses (line 103) | def plot_train_losses(clfs):
  function plot_train_scores (line 112) | def plot_train_scores(clfs):
  function plot_test_scores (line 122) | def plot_test_scores(clfs):
  function plot_dloss (line 132) | def plot_dloss(clfs):
  function get_max_squared_sum (line 150) | def get_max_squared_sum(X):

FILE: benchmarks/bench_saga.py
  function fit_single (line 28) | def fit_single(
  function _predict_proba (line 137) | def _predict_proba(lr, X):
  function exp (line 144) | def exp(
  function plot (line 238) | def plot(outname=None):

FILE: benchmarks/bench_sample_without_replacement.py
  function compute_time (line 18) | def compute_time(t_start, delta):
  function bench_sample (line 24) | def bench_sample(sampling, n_population, n_samples):

FILE: benchmarks/bench_sparsify.py
  function sparsity_ratio (line 54) | def sparsity_ratio(X):
  function benchmark_dense_predict (line 86) | def benchmark_dense_predict():
  function benchmark_sparse_predict (line 91) | def benchmark_sparse_predict():
  function score (line 97) | def score(y_test, y_pred, case):

FILE: benchmarks/bench_text_vectorizers.py
  function run_vectorizer (line 28) | def run_vectorizer(Vectorizer, X, **params):

FILE: benchmarks/bench_tree.py
  function bench_scikit_tree_classifier (line 28) | def bench_scikit_tree_classifier(X, Y):
  function bench_scikit_tree_regressor (line 45) | def bench_scikit_tree_regressor(X, Y):

FILE: benchmarks/bench_tsne_mnist.py
  function load_data (line 35) | def load_data(dtype=np.float32, order="C", shuffle=True, seed=0):
  function nn_accuracy (line 51) | def nn_accuracy(X, X_embedded, k=1):
  function tsne_fit_transform (line 59) | def tsne_fit_transform(model, data):
  function sanitize (line 64) | def sanitize(filename):
  function bhtsne (line 146) | def bhtsne(X):

FILE: build_tools/circle/list_versions.py
  function json_urlread (line 12) | def json_urlread(url):
  function human_readable_data_quantity (line 20) | def human_readable_data_quantity(quantity, multiple=1024):
  function get_file_extension (line 35) | def get_file_extension(version):
  function get_file_size (line 46) | def get_file_size(version):

FILE: build_tools/generate_authors_table.py
  function get (line 25) | def get(url):
  function get_contributors (line 41) | def get_contributors():
  function get_profile (line 97) | def get_profile(login):
  function key (line 122) | def key(profile):
  function generate_table (line 128) | def generate_table(contributors):
  function generate_list (line 149) | def generate_list(contributors):

FILE: build_tools/github/vendor.py
  function make_distributor_init_32_bits (line 22) | def make_distributor_init_32_bits(
  function make_distributor_init_64_bits (line 63) | def make_distributor_init_64_bits(
  function main (line 112) | def main(wheel_dirname, bitness):

FILE: doc/conf.py
  class SubSectionTitleOrder (line 326) | class SubSectionTitleOrder:
    method __init__ (line 333) | def __init__(self, src_dir):
    method __repr__ (line 337) | def __repr__(self):
    method __call__ (line 340) | def __call__(self, directory):
  function make_carousel_thumbs (line 396) | def make_carousel_thumbs(app, exception):
  function filter_search_index (line 410) | def filter_search_index(app, exception):
  function generate_min_dependency_table (line 431) | def generate_min_dependency_table(app):
  function generate_min_dependency_substitutions (line 481) | def generate_min_dependency_substitutions(app):
  function setup (line 504) | def setup(app):

FILE: doc/conftest.py
  function setup_labeled_faces (line 16) | def setup_labeled_faces():
  function setup_rcv1 (line 22) | def setup_rcv1():
  function setup_twenty_newsgroups (line 30) | def setup_twenty_newsgroups():
  function setup_working_with_text_data (line 36) | def setup_working_with_text_data():
  function setup_loading_other_datasets (line 45) | def setup_loading_other_datasets():
  function setup_compose (line 60) | def setup_compose():
  function setup_impute (line 67) | def setup_impute():
  function setup_grid_search (line 74) | def setup_grid_search():
  function setup_preprocessing (line 81) | def setup_preprocessing():
  function setup_unsupervised_learning (line 91) | def setup_unsupervised_learning():
  function skip_if_matplotlib_not_installed (line 102) | def skip_if_matplotlib_not_installed(fname):
  function pytest_runtest_setup (line 110) | def pytest_runtest_setup(item):
  function pytest_configure (line 153) | def pytest_configure(config):

FILE: doc/sphinxext/add_toctree_functions.py
  function add_toctree_functions (line 37) | def add_toctree_functions(app, pagename, templatename, context, doctree):
  function docutils_node_to_jinja (line 94) | def docutils_node_to_jinja(list_item, only_pages=False, numbered=False):
  function setup (line 157) | def setup(app):

FILE: doc/sphinxext/custom_references_resolver.py
  class CustomReferencesResolver (line 42) | class CustomReferencesResolver(ReferencesResolver):
    method resolve_anyref (line 43) | def resolve_anyref(self, refdoc, node, contnode):
    method create_node (line 102) | def create_node(self, result):
  function setup (line 117) | def setup(app):

FILE: doc/sphinxext/doi_role.py
  function reference_role (line 23) | def reference_role(typ, rawtext, text, lineno, inliner, options={}, cont...
  function setup_link_role (line 40) | def setup_link_role(app):
  function setup (line 47) | def setup(app):

FILE: doc/sphinxext/github_link.py
  function _get_git_revision (line 11) | def _get_git_revision():
  function _linkcode_resolve (line 20) | def _linkcode_resolve(domain, info, package, url_fmt, revision):
  function make_linkcode_resolve (line 70) | def make_linkcode_resolve(package, url_fmt):

FILE: doc/sphinxext/sphinx_issues.py
  function user_role (line 32) | def user_role(name, rawtext, text, lineno, inliner, options=None, conten...
  function cve_role (line 61) | def cve_role(name, rawtext, text, lineno, inliner, options=None, content...
  class IssueRole (line 78) | class IssueRole(object):
    method __init__ (line 82) | def __init__(
    method default_format_text (line 91) | def default_format_text(issue_no):
    method make_node (line 94) | def make_node(self, name, issue_no, config, options=None):
    method __call__ (line 133) | def __call__(
  function format_commit_text (line 177) | def format_commit_text(sha):
  function setup (line 195) | def setup(app):

FILE: doc/themes/scikit-learn-modern/static/js/searchtools.js
  function splitQuery (line 56) | function splitQuery(query) {
  function pulse (line 128) | function pulse() {
  function displayNextItem (line 272) | function displayNextItem() {

FILE: doc/tutorial/machine_learning_map/parse_path.py
  function Command (line 18) | def Command(char):
  function Arguments (line 22) | def Arguments(token):
  class CaselessPreservingLiteral (line 26) | class CaselessPreservingLiteral(CaselessLiteral):
    method __init__ (line 30) | def __init__( self, matchString ):
    method parseImpl (line 36) | def parseImpl( self, instring, loc, doActions=True ):
  function Sequence (line 46) | def Sequence(token):
  function convertToFloat (line 54) | def convertToFloat(s, loc, toks):
  function get_points (line 149) | def get_points(d):

FILE: doc/tutorial/machine_learning_map/pyparsing.py
  function _ustr (line 132) | def _ustr(obj):
  function _xml_escape (line 163) | def _xml_escape(data):
  class _Constants (line 173) | class _Constants(object):
  class ParseBaseException (line 183) | class ParseBaseException(Exception):
    method __init__ (line 187) | def __init__( self, pstr, loc=0, msg=None, elem=None ):
    method _from_exception (line 199) | def _from_exception(cls, pe):
    method __getattr__ (line 206) | def __getattr__( self, aname ):
    method __str__ (line 221) | def __str__( self ):
    method __repr__ (line 224) | def __repr__( self ):
    method markInputline (line 226) | def markInputline( self, markerString = ">!<" ):
    method __dir__ (line 236) | def __dir__(self):
  class ParseException (line 239) | class ParseException(ParseBaseException):
  class ParseFatalException (line 260) | class ParseFatalException(ParseBaseException):
  class ParseSyntaxException (line 265) | class ParseSyntaxException(ParseFatalException):
  class RecursiveGrammarException (line 284) | class RecursiveGrammarException(Exception):
    method __init__ (line 286) | def __init__( self, parseElementList ):
    method __str__ (line 289) | def __str__( self ):
  class _ParseResultsWithOffset (line 292) | class _ParseResultsWithOffset(object):
    method __init__ (line 293) | def __init__(self,p1,p2):
    method __getitem__ (line 295) | def __getitem__(self,i):
    method __repr__ (line 297) | def __repr__(self):
    method setOffset (line 299) | def setOffset(self,i):
  class ParseResults (line 302) | class ParseResults(object):
    method __new__ (line 341) | def __new__(cls, toklist=None, name=None, asList=True, modal=True ):
    method __init__ (line 350) | def __init__( self, toklist=None, name=None, asList=True, modal=True, ...
    method __getitem__ (line 389) | def __getitem__( self, i ):
    method __setitem__ (line 398) | def __setitem__( self, k, v, isinstance=isinstance ):
    method __delitem__ (line 411) | def __delitem__( self, i ):
    method __contains__ (line 432) | def __contains__( self, k ):
    method __len__ (line 435) | def __len__( self ): return len( self.__toklist )
    method __bool__ (line 436) | def __bool__(self): return ( not not self.__toklist )
    method __iter__ (line 438) | def __iter__( self ): return iter( self.__toklist )
    method __reversed__ (line 439) | def __reversed__( self ): return iter( self.__toklist[::-1] )
    method _iterkeys (line 440) | def _iterkeys( self ):
    method _itervalues (line 446) | def _itervalues( self ):
    method _iteritems (line 449) | def _iteritems( self ):
    method keys (line 472) | def keys( self ):
    method values (line 476) | def values( self ):
    method items (line 480) | def items( self ):
    method haskeys (line 484) | def haskeys( self ):
    method pop (line 489) | def pop( self, *args, **kwargs):
    method get (line 541) | def get(self, key, defaultValue=None):
    method insert (line 563) | def insert( self, index, insStr ):
    method append (line 583) | def append( self, item ):
    method extend (line 597) | def extend( self, itemseq ):
    method clear (line 615) | def clear( self ):
    method __getattr__ (line 622) | def __getattr__( self, name ):
    method __add__ (line 636) | def __add__( self, other ):
    method __iadd__ (line 641) | def __iadd__( self, other ):
    method __radd__ (line 657) | def __radd__(self, other):
    method __repr__ (line 665) | def __repr__( self ):
    method __str__ (line 668) | def __str__( self ):
    method _asStringList (line 671) | def _asStringList( self, sep='' ):
    method asList (line 682) | def asList( self ):
    method asDict (line 698) | def asDict( self ):
    method copy (line 733) | def copy( self ):
    method asXML (line 744) | def asXML( self, doctag=None, namedItemsOnly=False, indent="", formatt...
    method __lookup (line 805) | def __lookup(self,sub):
    method getName (line 812) | def getName(self):
    method dump (line 849) | def dump(self, indent='', depth=0, full=True):
    method pprint (line 894) | def pprint(self, *args, **kwargs):
    method __getstate__ (line 918) | def __getstate__(self):
    method __setstate__ (line 925) | def __setstate__(self,state):
    method __getnewargs__ (line 938) | def __getnewargs__(self):
    method __dir__ (line 941) | def __dir__(self):
  function col (line 946) | def col (loc,strg):
  function lineno (line 959) | def lineno(loc,strg):
  function line (line 971) | def line( loc, strg ):
  function _defaultStartDebugAction (line 981) | def _defaultStartDebugAction( instring, loc, expr ):
  function _defaultSuccessDebugAction (line 984) | def _defaultSuccessDebugAction( instring, startloc, endloc, expr, toks ):
  function _defaultExceptionDebugAction (line 987) | def _defaultExceptionDebugAction( instring, loc, expr, exc ):
  function nullDebugAction (line 990) | def nullDebugAction(*args):
  function _trim_arity (line 1017) | def _trim_arity(func, maxargs=2):
  class ParserElement (line 1075) | class ParserElement(object):
    method setDefaultWhitespaceChars (line 1081) | def setDefaultWhitespaceChars( chars ):
    method inlineLiteralsUsing (line 1096) | def inlineLiteralsUsing(cls):
    method __init__ (line 1116) | def __init__( self, savelist=False ):
    method copy (line 1139) | def copy( self ):
    method setName (line 1162) | def setName( self, name ):
    method setResultsName (line 1176) | def setResultsName( self, name, listAllMatches=False ):
    method setBreak (line 1204) | def setBreak(self,breakFlag = True):
    method setParseAction (line 1222) | def setParseAction( self, *fns, **kwargs ):
    method addParseAction (line 1260) | def addParseAction( self, *fns, **kwargs ):
    method addCondition (line 1270) | def addCondition(self, *fns, **kwargs):
    method setFailAction (line 1297) | def setFailAction( self, fn ):
    method _skipIgnorables (line 1310) | def _skipIgnorables( self, instring, loc ):
    method preParse (line 1323) | def preParse( self, instring, loc ):
    method parseImpl (line 1335) | def parseImpl( self, instring, loc, doActions=True ):
    method postParse (line 1338) | def postParse( self, instring, loc, tokenlist ):
    method _parseNoCache (line 1342) | def _parseNoCache( self, instring, loc, doActions=True, callPreParse=T...
    method tryParse (line 1414) | def tryParse( self, instring, loc ):
    method canParseNext (line 1420) | def canParseNext(self, instring, loc):
    class _UnboundedCache (line 1428) | class _UnboundedCache(object):
      method __init__ (line 1429) | def __init__(self):
    class _FifoCache (line 1451) | class _FifoCache(object):
      method __init__ (line 1452) | def __init__(self, size):
      method __init__ (line 1481) | def __init__(self, size):
    class _FifoCache (line 1480) | class _FifoCache(object):
      method __init__ (line 1452) | def __init__(self, size):
      method __init__ (line 1481) | def __init__(self, size):
    method _parseCache (line 1515) | def _parseCache( self, instring, loc, doActions=True, callPreParse=Tru...
    method resetCache (line 1541) | def resetCache():
    method enablePackrat (line 1547) | def enablePackrat(cache_size_limit=128):
    method parseString (line 1581) | def parseString( self, instring, parseAll=False ):
    method scanString (line 1631) | def scanString( self, instring, maxMatches=_MAX_INT, overlap=False ):
    method transformString (line 1702) | def transformString( self, instring ):
    method searchString (line 1745) | def searchString( self, instring, maxMatches=_MAX_INT ):
    method split (line 1772) | def split(self, instring, maxsplit=_MAX_INT, includeSeparators=False):
    method __add__ (line 1794) | def __add__(self, other ):
    method __radd__ (line 1814) | def __radd__(self, other ):
    method __sub__ (line 1826) | def __sub__(self, other):
    method __rsub__ (line 1838) | def __rsub__(self, other ):
    method __mul__ (line 1850) | def __mul__(self,other):
    method __rmul__ (line 1918) | def __rmul__(self, other):
    method __or__ (line 1921) | def __or__(self, other ):
    method __ror__ (line 1933) | def __ror__(self, other ):
    method __xor__ (line 1945) | def __xor__(self, other ):
    method __rxor__ (line 1957) | def __rxor__(self, other ):
    method __and__ (line 1969) | def __and__(self, other ):
    method __rand__ (line 1981) | def __rand__(self, other ):
    method __invert__ (line 1993) | def __invert__( self ):
    method __call__ (line 1999) | def __call__(self, name=None):
    method suppress (line 2018) | def suppress( self ):
    method leaveWhitespace (line 2025) | def leaveWhitespace( self ):
    method setWhitespaceChars (line 2034) | def setWhitespaceChars( self, chars ):
    method parseWithTabs (line 2043) | def parseWithTabs( self ):
    method ignore (line 2052) | def ignore( self, other ):
    method setDebugActions (line 2075) | def setDebugActions( self, startAction, successAction, exceptionAction ):
    method setDebug (line 2085) | def setDebug( self, flag=True ):
    method __str__ (line 2126) | def __str__( self ):
    method __repr__ (line 2129) | def __repr__( self ):
    method streamline (line 2132) | def streamline( self ):
    method checkRecursion (line 2137) | def checkRecursion( self, parseElementList ):
    method validate (line 2140) | def validate( self, validateTrace=[] ):
    method parseFile (line 2146) | def parseFile( self, file_or_filename, parseAll=False ):
    method __eq__ (line 2166) | def __eq__(self,other):
    method __ne__ (line 2174) | def __ne__(self,other):
    method __hash__ (line 2177) | def __hash__(self):
    method __req__ (line 2180) | def __req__(self,other):
    method __rne__ (line 2183) | def __rne__(self,other):
    method matches (line 2186) | def matches(self, testString, parseAll=True):
    method runTests (line 2205) | def runTests(self, tests, parseAll=True, comment='#', fullDump=True, p...
  class Token (line 2337) | class Token(ParserElement):
    method __init__ (line 2341) | def __init__( self ):
  class Empty (line 2345) | class Empty(Token):
    method __init__ (line 2349) | def __init__( self ):
  class NoMatch (line 2356) | class NoMatch(Token):
    method __init__ (line 2360) | def __init__( self ):
    method parseImpl (line 2367) | def parseImpl( self, instring, loc, doActions=True ):
  class Literal (line 2371) | class Literal(Token):
    method __init__ (line 2385) | def __init__( self, matchString ):
    method parseImpl (line 2404) | def parseImpl( self, instring, loc, doActions=True ):
  class Keyword (line 2412) | class Keyword(Token):
    method __init__ (line 2431) | def __init__( self, matchString, identChars=None, caseless=False ):
    method parseImpl (line 2452) | def parseImpl( self, instring, loc, doActions=True ):
    method copy (line 2466) | def copy(self):
    method setDefaultKeywordChars (line 2472) | def setDefaultKeywordChars( chars ):
  class CaselessLiteral (line 2477) | class CaselessLiteral(Literal):
    method __init__ (line 2488) | def __init__( self, matchString ):
    method parseImpl (line 2495) | def parseImpl( self, instring, loc, doActions=True ):
  class CaselessKeyword (line 2500) | class CaselessKeyword(Keyword):
    method __init__ (line 2509) | def __init__( self, matchString, identChars=None ):
    method parseImpl (line 2512) | def parseImpl( self, instring, loc, doActions=True ):
  class CloseMatch (line 2518) | class CloseMatch(Token):
    method __init__ (line 2543) | def __init__(self, match_string, maxMismatches=1):
    method parseImpl (line 2552) | def parseImpl( self, instring, loc, doActions=True ):
  class Word (line 2579) | class Word(Token):
    method __init__ (line 2626) | def __init__( self, initChars, bodyChars=None, min=1, max=0, exact=0, ...
    method parseImpl (line 2680) | def parseImpl( self, instring, loc, doActions=True ):
    method __str__ (line 2715) | def __str__( self ):
  class Regex (line 2738) | class Regex(Token):
    method __init__ (line 2752) | def __init__( self, pattern, flags=0):
    method parseImpl (line 2786) | def parseImpl( self, instring, loc, doActions=True ):
    method __str__ (line 2799) | def __str__( self ):
  class QuotedString (line 2811) | class QuotedString(Token):
    method __init__ (line 2836) | def __init__( self, quoteChar, escChar=None, escQuote=None, multiline=...
    method parseImpl (line 2901) | def parseImpl( self, instring, loc, doActions=True ):
    method __str__ (line 2936) | def __str__( self ):
  class CharsNotIn (line 2948) | class CharsNotIn(Token):
    method __init__ (line 2964) | def __init__( self, notChars, min=1, max=0, exact=0 ):
    method parseImpl (line 2988) | def parseImpl( self, instring, loc, doActions=True ):
    method __str__ (line 3005) | def __str__( self ):
  class White (line 3019) | class White(Token):
    method __init__ (line 3034) | def __init__(self, ws=" \t\r\n", min=1, max=0, exact=0):
    method parseImpl (line 3054) | def parseImpl( self, instring, loc, doActions=True ):
  class _PositionToken (line 3070) | class _PositionToken(Token):
    method __init__ (line 3071) | def __init__( self ):
  class GoToColumn (line 3077) | class GoToColumn(_PositionToken):
    method __init__ (line 3081) | def __init__( self, colno ):
    method preParse (line 3085) | def preParse( self, instring, loc ):
    method parseImpl (line 3094) | def parseImpl( self, instring, loc, doActions=True ):
  class LineStart (line 3103) | class LineStart(_PositionToken):
    method __init__ (line 3124) | def __init__( self ):
    method parseImpl (line 3128) | def parseImpl( self, instring, loc, doActions=True ):
  class LineEnd (line 3133) | class LineEnd(_PositionToken):
    method __init__ (line 3137) | def __init__( self ):
    method parseImpl (line 3142) | def parseImpl( self, instring, loc, doActions=True ):
  class StringStart (line 3153) | class StringStart(_PositionToken):
    method __init__ (line 3157) | def __init__( self ):
    method parseImpl (line 3161) | def parseImpl( self, instring, loc, doActions=True ):
  class StringEnd (line 3168) | class StringEnd(_PositionToken):
    method __init__ (line 3172) | def __init__( self ):
    method parseImpl (line 3176) | def parseImpl( self, instring, loc, doActions=True ):
  class WordStart (line 3186) | class WordStart(_PositionToken):
    method __init__ (line 3194) | def __init__(self, wordChars = printables):
    method parseImpl (line 3199) | def parseImpl(self, instring, loc, doActions=True ):
  class WordEnd (line 3206) | class WordEnd(_PositionToken):
    method __init__ (line 3214) | def __init__(self, wordChars = printables):
    method parseImpl (line 3220) | def parseImpl(self, instring, loc, doActions=True ):
  class ParseExpression (line 3229) | class ParseExpression(ParserElement):
    method __init__ (line 3233) | def __init__( self, exprs, savelist = False ):
    method __getitem__ (line 3253) | def __getitem__( self, i ):
    method append (line 3256) | def append( self, other ):
    method leaveWhitespace (line 3261) | def leaveWhitespace( self ):
    method ignore (line 3270) | def ignore( self, other ):
    method __str__ (line 3282) | def __str__( self ):
    method streamline (line 3292) | def streamline( self ):
    method setResultsName (line 3326) | def setResultsName( self, name, listAllMatches=False ):
    method validate (line 3330) | def validate( self, validateTrace=[] ):
    method copy (line 3336) | def copy(self):
  class And (line 3341) | class And(ParseExpression):
    class _ErrorStop (line 3357) | class _ErrorStop(Empty):
      method __init__ (line 3358) | def __init__(self, *args, **kwargs):
    method __init__ (line 3363) | def __init__( self, exprs, savelist = True ):
    method parseImpl (line 3370) | def parseImpl( self, instring, loc, doActions=True ):
    method __iadd__ (line 3395) | def __iadd__(self, other ):
    method checkRecursion (line 3400) | def checkRecursion( self, parseElementList ):
    method __str__ (line 3407) | def __str__( self ):
  class Or (line 3417) | class Or(ParseExpression):
    method __init__ (line 3431) | def __init__( self, exprs, savelist = False ):
    method parseImpl (line 3438) | def parseImpl( self, instring, loc, doActions=True ):
    method __ixor__ (line 3476) | def __ixor__(self, other ):
    method __str__ (line 3481) | def __str__( self ):
    method checkRecursion (line 3490) | def checkRecursion( self, parseElementList ):
  class MatchFirst (line 3496) | class MatchFirst(ParseExpression):
    method __init__ (line 3513) | def __init__( self, exprs, savelist = False ):
    method parseImpl (line 3520) | def parseImpl( self, instring, loc, doActions=True ):
    method __ior__ (line 3544) | def __ior__(self, other ):
    method __str__ (line 3549) | def __str__( self ):
    method checkRecursion (line 3558) | def checkRecursion( self, parseElementList ):
  class Each (line 3564) | class Each(ParseExpression):
    method __init__ (line 3618) | def __init__( self, exprs, savelist = True ):
    method parseImpl (line 3624) | def parseImpl( self, instring, loc, doActions=True ):
    method __str__ (line 3673) | def __str__( self ):
    method checkRecursion (line 3682) | def checkRecursion( self, parseElementList ):
  class ParseElementEnhance (line 3688) | class ParseElementEnhance(ParserElement):
    method __init__ (line 3692) | def __init__( self, expr, savelist=False ):
    method parseImpl (line 3710) | def parseImpl( self, instring, loc, doActions=True ):
    method leaveWhitespace (line 3716) | def leaveWhitespace( self ):
    method ignore (line 3723) | def ignore( self, other ):
    method streamline (line 3735) | def streamline( self ):
    method checkRecursion (line 3741) | def checkRecursion( self, parseElementList ):
    method validate (line 3748) | def validate( self, validateTrace=[] ):
    method __str__ (line 3754) | def __str__( self ):
  class FollowedBy (line 3765) | class FollowedBy(ParseElementEnhance):
    method __init__ (line 3782) | def __init__( self, expr ):
    method parseImpl (line 3786) | def parseImpl( self, instring, loc, doActions=True ):
  class NotAny (line 3791) | class NotAny(ParseElementEnhance):
    method __init__ (line 3802) | def __init__( self, expr ):
    method parseImpl (line 3809) | def parseImpl( self, instring, loc, doActions=True ):
    method __str__ (line 3814) | def __str__( self ):
  class _MultipleMatch (line 3823) | class _MultipleMatch(ParseElementEnhance):
    method __init__ (line 3824) | def __init__( self, expr, stopOn=None):
    method parseImpl (line 3832) | def parseImpl( self, instring, loc, doActions=True ):
  class OneOrMore (line 3861) | class OneOrMore(_MultipleMatch):
    method __str__ (line 3887) | def __str__( self ):
  class ZeroOrMore (line 3896) | class ZeroOrMore(_MultipleMatch):
    method __init__ (line 3908) | def __init__( self, expr, stopOn=None):
    method parseImpl (line 3912) | def parseImpl( self, instring, loc, doActions=True ):
    method __str__ (line 3918) | def __str__( self ):
  class _NullToken (line 3927) | class _NullToken(object):
    method __bool__ (line 3928) | def __bool__(self):
    method __str__ (line 3931) | def __str__(self):
  class Optional (line 3935) | class Optional(ParseElementEnhance):
    method __init__ (line 3970) | def __init__( self, expr, default=_optionalNotMatched ):
    method parseImpl (line 3976) | def parseImpl( self, instring, loc, doActions=True ):
    method __str__ (line 3990) | def __str__( self ):
  class SkipTo (line 3999) | class SkipTo(ParseElementEnhance):
    method __init__ (line 4054) | def __init__( self, other, include=False, ignore=None, failOn=None ):
    method parseImpl (line 4067) | def parseImpl( self, instring, loc, doActions=True ):
  class Forward (line 4114) | class Forward(ParseElementEnhance):
    method __init__ (line 4133) | def __init__( self, other=None ):
    method __lshift__ (line 4136) | def __lshift__( self, other ):
    method __ilshift__ (line 4149) | def __ilshift__(self, other):
    method leaveWhitespace (line 4152) | def leaveWhitespace( self ):
    method streamline (line 4156) | def streamline( self ):
    method validate (line 4163) | def validate( self, validateTrace=[] ):
    method __str__ (line 4170) | def __str__( self ):
    method copy (line 4187) | def copy(self):
  class _ForwardNoRecurse (line 4195) | class _ForwardNoRecurse(Forward):
    method __str__ (line 4196) | def __str__( self ):
  class TokenConverter (line 4199) | class TokenConverter(ParseElementEnhance):
    method __init__ (line 4203) | def __init__( self, expr, savelist=False ):
  class Combine (line 4207) | class Combine(TokenConverter):
    method __init__ (line 4224) | def __init__( self, expr, joinString="", adjacent=True ):
    method ignore (line 4234) | def ignore( self, other ):
    method postParse (line 4241) | def postParse( self, instring, loc, tokenlist ):
  class Group (line 4251) | class Group(TokenConverter):
    method __init__ (line 4265) | def __init__( self, expr ):
    method postParse (line 4269) | def postParse( self, instring, loc, tokenlist ):
  class Dict (line 4272) | class Dict(TokenConverter):
    method __init__ (line 4308) | def __init__( self, expr ):
    method postParse (line 4312) | def postParse( self, instring, loc, tokenlist ):
  class Suppress (line 4337) | class Suppress(TokenConverter):
    method postParse (line 4356) | def postParse( self, instring, loc, tokenlist ):
    method suppress (line 4359) | def suppress( self ):
  class OnlyOnce (line 4363) | class OnlyOnce(object):
    method __init__ (line 4367) | def __init__(self, methodCall):
    method __call__ (line 4370) | def __call__(self,s,l,t):
    method reset (line 4376) | def reset(self):
  function traceParseAction (line 4379) | def traceParseAction(f):
  function delimitedList (line 4423) | def delimitedList( expr, delim=",", combine=False ):
  function countedArray (line 4442) | def countedArray( expr, intExpr=None ):
  function _flatten (line 4473) | def _flatten(L):
  function matchPreviousLiteral (line 4482) | def matchPreviousLiteral(expr):
  function matchPreviousExpr (line 4510) | def matchPreviousExpr(expr):
  function _escapeRegexRangeChars (line 4538) | def _escapeRegexRangeChars(s):
  function oneOf (line 4546) | def oneOf( strs, caseless=False, useRegex=True ):
  function dictOf (line 4619) | def dictOf( key, value ):
  function originalTextFor (line 4654) | def originalTextFor(expr, asString=True):
  function ungroup (line 4691) | def ungroup(expr):
  function locatedExpr (line 4698) | def locatedExpr(expr):
  function srange (line 4736) | def srange(s):
  function matchOnlyAtCol (line 4760) | def matchOnlyAtCol(n):
  function replaceWith (line 4770) | def replaceWith(replStr):
  function removeQuotes (line 4784) | def removeQuotes(s,l,t):
  function tokenMap (line 4798) | def tokenMap(func, *args):
  function _makeTags (line 4848) | def _makeTags(tagStr, xml):
  function makeHTMLTags (line 4877) | def makeHTMLTags(tagStr):
  function makeXMLTags (line 4896) | def makeXMLTags(tagStr):
  function withAttribute (line 4905) | def withAttribute(*args,**attrDict):
  function withClass (line 4970) | def withClass(classname, namespace=''):
  function infixNotation (line 5009) | def infixNotation( baseExpr, opList, lpar=Suppress('('), rpar=Suppress('...
  function nestedExpr (line 5130) | def nestedExpr(opener="(", closer=")", content=None, ignoreExpr=quotedSt...
  function indentedBlock (line 5220) | def indentedBlock(blockStatementExpr, indentStack, indent=True):
  function replaceHTMLEntity (line 5340) | def replaceHTMLEntity(t):
  class pyparsing_common (line 5372) | class pyparsing_common:
    method convertToDate (line 5566) | def convertToDate(fmt="%Y-%m-%d"):
    method convertToDatetime (line 5588) | def convertToDatetime(fmt="%Y-%m-%dT%H:%M:%S.%f"):
    method stripHTMLTags (line 5620) | def stripHTMLTags(s, l, tokens):

FILE: examples/applications/plot_cyclical_feature_engineering.py
  function evaluate (line 222) | def evaluate(model, X, y, cv):
  function sin_transformer (line 354) | def sin_transformer(period):
  function cos_transformer (line 358) | def cos_transformer(period):
  function periodic_spline_transformer (line 431) | def periodic_spline_transformer(period, n_splines=None, degree=3):

FILE: examples/applications/plot_digits_denoising.py
  function plot_digits (line 73) | def plot_digits(X, title):

FILE: examples/applications/plot_face_recognition.py
  function plot_gallery (line 134) | def plot_gallery(images, titles, h, w, n_row=3, n_col=4):
  function title (line 149) | def title(y_pred, y_test, target_names, i):

FILE: examples/applications/plot_model_complexity_influence.py
  function generate_data (line 71) | def generate_data(case):
  function benchmark_influence (line 102) | def benchmark_influence(conf):
  function _count_nonzero_coefficients (line 154) | def _count_nonzero_coefficients(estimator):
  function plot_influence (line 228) | def plot_influence(conf, mse_values, prediction_times, complexities):

FILE: examples/applications/plot_out_of_core_classification.py
  function _not_in_sphinx (line 43) | def _not_in_sphinx():
  class ReutersParser (line 57) | class ReutersParser(HTMLParser):
    method __init__ (line 60) | def __init__(self, encoding="latin-1"):
    method handle_starttag (line 65) | def handle_starttag(self, tag, attrs):
    method handle_endtag (line 69) | def handle_endtag(self, tag):
    method _reset (line 73) | def _reset(self):
    method parse (line 83) | def parse(self, fd):
    method handle_data (line 92) | def handle_data(self, data):
    method start_reuters (line 100) | def start_reuters(self, attributes):
    method end_reuters (line 103) | def end_reuters(self):
    method start_title (line 110) | def start_title(self, attributes):
    method end_title (line 113) | def end_title(self):
    method start_body (line 116) | def start_body(self, attributes):
    method end_body (line 119) | def end_body(self):
    method start_topics (line 122) | def start_topics(self, attributes):
    method end_topics (line 125) | def end_topics(self):
    method start_d (line 128) | def start_d(self, attributes):
    method end_d (line 131) | def end_d(self):
  function stream_reuters_documents (line 137) | def stream_reuters_documents(data_path=None):
  function get_minibatch (line 212) | def get_minibatch(doc_iter, size, pos_class=positive_class):
  function iter_minibatches (line 229) | def iter_minibatches(doc_iter, minibatch_size):
  function progress (line 253) | def progress(cls_name, stats):
  function plot_accuracy (line 336) | def plot_accuracy(x, y, x_legend):
  function autolabel (line 389) | def autolabel(rectangles):

FILE: examples/applications/plot_prediction_latency.py
  function _not_in_sphinx (line 36) | def _not_in_sphinx():
  function atomic_benchmark_estimator (line 41) | def atomic_benchmark_estimator(estimator, X_test, verbose=False):
  function bulk_benchmark_estimator (line 60) | def bulk_benchmark_estimator(estimator, X_test, n_bulk_repeats, verbose):
  function benchmark_estimator (line 79) | def benchmark_estimator(estimator, X_test, n_bulk_repeats=30, verbose=Fa...
  function generate_dataset (line 100) | def generate_dataset(n_train, n_test, n_features, noise=0.1, verbose=Fal...
  function boxplot_runtimes (line 129) | def boxplot_runtimes(runtimes, pred_type, configuration):
  function benchmark (line 172) | def benchmark(configuration):
  function n_feature_influence (line 195) | def n_feature_influence(estimators, n_train, n_test, n_features, percent...
  function plot_n_features_influence (line 227) | def plot_n_features_influence(percentiles, percentile):
  function benchmark_throughputs (line 246) | def benchmark_throughputs(configuration, duration_secs=0.1):
  function plot_benchmark_throughput (line 263) | def plot_benchmark_throughput(throughputs, configuration):

FILE: examples/applications/plot_species_distribution_modeling.py
  function construct_grids (line 63) | def construct_grids(batch):
  function create_species_bunch (line 90) | def create_species_bunch(species_name, train, test, coverages, xgrid, yg...
  function plot_species_distribution (line 113) | def plot_species_distribution(

FILE: examples/applications/plot_tomography_l1_reconstruction.py
  function _weights (line 50) | def _weights(x, dx=1, orig=0):
  function _generate_center_coordinates (line 57) | def _generate_center_coordinates(l_x):
  function build_projection_operator (line 65) | def build_projection_operator(l_x, n_dir):
  function generate_synthetic_data (line 97) | def generate_synthetic_data():

FILE: examples/applications/plot_topics_extraction_with_nmf_lda.py
  function plot_top_words (line 42) | def plot_top_words(model, feature_names, n_top_words, title):

FILE: examples/applications/svm_gui.py
  class Model (line 47) | class Model:
    method __init__ (line 53) | def __init__(self):
    method changed (line 60) | def changed(self, event):
    method add_observer (line 65) | def add_observer(self, observer):
    method set_surface (line 69) | def set_surface(self, surface):
    method dump_svmlight_file (line 72) | def dump_svmlight_file(self, file):
  class Controller (line 79) | class Controller:
    method __init__ (line 80) | def __init__(self, model):
    method fit (line 87) | def fit(self):
    method decision_surface (line 124) | def decision_surface(self, cls):
    method clear_data (line 133) | def clear_data(self):
    method add_example (line 138) | def add_example(self, x, y, label):
    method refit (line 145) | def refit(self):
  class View (line 151) | class View:
    method __init__ (line 154) | def __init__(self, root, controller):
    method plot_kernels (line 181) | def plot_kernels(self):
    method onclick (line 186) | def onclick(self, event):
    method update_example (line 193) | def update_example(self, model, idx):
    method update (line 201) | def update(self, event, model):
    method remove_surface (line 224) | def remove_surface(self):
    method plot_support_vectors (line 235) | def plot_support_vectors(self, support_vectors):
    method plot_decision_surface (line 248) | def plot_decision_surface(self, surface, type):
  class ControllBar (line 270) | class ControllBar:
    method __init__ (line 271) | def __init__(self, root, controller):
  function get_parser (line 353) | def get_parser():
  function main (line 367) | def main(argv):

FILE: examples/applications/wikipedia_principal_eigenvector.py
  function index (line 75) | def index(redirects, index_map, k):
  function short_name (line 85) | def short_name(nt_uri):
  function get_redirects (line 90) | def get_redirects(redirects_filename):
  function get_adjacency_matrix (line 122) | def get_adjacency_matrix(redirects_filename, page_links_filename, limit=...
  function centrality_scores (line 181) | def centrality_scores(X, alpha=0.85, max_iter=100, tol=1e-10):

FILE: examples/bicluster/plot_bicluster_newsgroups.py
  function number_normalizer (line 39) | def number_normalizer(tokens):
  class NumberNormalizingVectorizer (line 49) | class NumberNormalizingVectorizer(TfidfVectorizer):
    method build_tokenizer (line 50) | def build_tokenizer(self):
  function bicluster_ncut (line 112) | def bicluster_ncut(i):
  function most_common (line 127) | def most_common(d):

FILE: examples/calibration/plot_calibration_curve.py
  class NaivelyCalibratedLinearSVC (line 203) | class NaivelyCalibratedLinearSVC(LinearSVC):
    method fit (line 207) | def fit(self, X, y):
    method predict_proba (line 213) | def predict_proba(self, X):

FILE: examples/calibration/plot_compare_calibration.py
  class NaivelyCalibratedLinearSVC (line 65) | class NaivelyCalibratedLinearSVC(LinearSVC):
    method fit (line 69) | def fit(self, X, y):
    method predict_proba (line 75) | def predict_proba(self, X):

FILE: examples/classification/plot_lda.py
  function generate_data (line 26) | def generate_data(n_samples, n_features):

FILE: examples/classification/plot_lda_qda.py
  function dataset_fixed_cov (line 38) | def dataset_fixed_cov():
  function dataset_cov (line 51) | def dataset_cov():
  function plot_data (line 66) | def plot_data(lda, X, y, y_pred, fig_index):
  function plot_ellipse (line 125) | def plot_ellipse(splot, mean, cov, color):
  function plot_lda_cov (line 147) | def plot_lda_cov(lda, splot):
  function plot_qda_cov (line 152) | def plot_qda_cov(qda, splot):

FILE: examples/cluster/plot_adjusted_for_chance_measures.py
  function uniform_labelings_scores (line 33) | def uniform_labelings_scores(
  function ami_score (line 59) | def ami_score(U, V):

FILE: examples/cluster/plot_agglomerative_clustering_metrics.py
  function sqr (line 53) | def sqr(x):

FILE: examples/cluster/plot_agglomerative_dendrogram.py
  function plot_dendrogram (line 20) | def plot_dendrogram(model, **kwargs):

FILE: examples/cluster/plot_color_quantization.py
  function recreate_image (line 72) | def recreate_image(codebook, labels, w, h):

FILE: examples/cluster/plot_digits_linkage.py
  function plot_clustering (line 48) | def plot_clustering(X_red, labels, title=None):

FILE: examples/cluster/plot_inductive_clustering.py
  function _classifier_has (line 40) | def _classifier_has(attr):
  class InductiveClusterer (line 53) | class InductiveClusterer(BaseEstimator):
    method __init__ (line 54) | def __init__(self, clusterer, classifier):
    method fit (line 58) | def fit(self, X, y=None):
    method predict (line 66) | def predict(self, X):
    method decision_function (line 71) | def decision_function(self, X):
  function plot_scatter (line 76) | def plot_scatter(X, color, alpha=0.5):

FILE: examples/cluster/plot_kmeans_digits.py
  function bench_k_means (line 61) | def bench_k_means(kmeans, name, data, labels):

FILE: examples/cluster/plot_kmeans_stability_low_dim_dense.py
  function make_data (line 55) | def make_data(random_state, n_samples_per_center, grid_size, scale):

FILE: examples/compose/plot_column_transformer.py
  function subject_body_extractor (line 81) | def subject_body_extractor(posts):
  function text_stats (line 110) | def text_stats(posts):

FILE: examples/datasets/plot_random_multilabel_dataset.py
  function plot_2d (line 61) | def plot_2d(ax, n_labels=1, n_classes=3, length=50):

FILE: examples/decomposition/plot_faces_decomposition.py
  function plot_gallery (line 47) | def plot_gallery(title, images, n_col=n_col, n_row=n_row, cmap=plt.cm.gr...

FILE: examples/decomposition/plot_ica_vs_pca.py
  function plot_samples (line 64) | def plot_samples(S, axis_list=None):

FILE: examples/decomposition/plot_image_denoising.py
  function show_with_diff (line 105) | def show_with_diff(image, reference, title):

FILE: examples/decomposition/plot_pca_3d.py
  function pdf (line 33) | def pdf(x):
  function plot_figs (line 57) | def plot_figs(fig_num, elev, azim):

FILE: examples/decomposition/plot_pca_vs_fa_model_selection.py
  function compute_scores (line 63) | def compute_scores(X):
  function shrunk_cov_score (line 77) | def shrunk_cov_score(X):
  function lw_score (line 83) | def lw_score(X):

FILE: examples/decomposition/plot_sparse_coding.py
  function ricker_function (line 26) | def ricker_function(resolution, center, width):
  function ricker_matrix (line 37) | def ricker_matrix(width, resolution, n_components):

FILE: examples/ensemble/plot_bias_variance.py
  function f (line 94) | def f(x):
  function generate (line 100) | def generate(n_samples, noise, n_repeat=1):

FILE: examples/ensemble/plot_feature_transformation.py
  function rf_apply (line 111) | def rf_apply(X, model):
  function gbdt_apply (line 126) | def gbdt_apply(X, model):

FILE: examples/ensemble/plot_gradient_boosting_categorical.py
  function plot_results (line 143) | def plot_results(figure_title):

FILE: examples/ensemble/plot_gradient_boosting_early_stopping.py
  function autolabel (line 113) | def autolabel(rects, n_estimators):

FILE: examples/ensemble/plot_gradient_boosting_oob.py
  function heldout_score (line 75) | def heldout_score(clf, X_test, y_test):
  function cv_estimate (line 83) | def cv_estimate(n_splits=None):

FILE: examples/ensemble/plot_gradient_boosting_quantile.py
  function f (line 18) | def f(x):
  function highlight_min (line 132) | def highlight_min(x):
  function coverage_fraction (line 197) | def coverage_fraction(y, y_low, y_high):

FILE: examples/ensemble/plot_stack_predictors.py
  function load_ames_housing (line 51) | def load_ames_housing():
  function plot_regression_results (line 219) | def plot_regression_results(ax, y_true, y_pred, title, scores, elapsed_t...

FILE: examples/gaussian_process/plot_gpc_isoprobability.py
  function g (line 29) | def g(x):

FILE: examples/gaussian_process/plot_gpr_noisy.py
  function target_generator (line 26) | def target_generator(X, add_noise=False):

FILE: examples/gaussian_process/plot_gpr_on_structured_data.py
  class SequenceKernel (line 50) | class SequenceKernel(GenericKernelMixin, Kernel):
    method __init__ (line 55) | def __init__(self, baseline_similarity=0.5, baseline_similarity_bounds...
    method hyperparameter_baseline_similarity (line 60) | def hyperparameter_baseline_similarity(self):
    method _f (line 65) | def _f(self, s1, s2):
    method _g (line 73) | def _g(self, s1, s2):
    method __call__ (line 79) | def __call__(self, X, Y=None, eval_gradient=False):
    method diag (line 91) | def diag(self, X):
    method is_stationary (line 94) | def is_stationary(self):
    method clone_with_theta (line 97) | def clone_with_theta(self, theta):

FILE: examples/gaussian_process/plot_gpr_prior_posterior.py
  function plot_gpr_samples (line 37) | def plot_gpr_samples(gpr_model, n_samples, ax):

FILE: examples/impute/plot_missing_values.py
  function add_missing_values (line 59) | def add_missing_values(X_full, y_full):
  function get_scores_for_imputer (line 113) | def get_scores_for_imputer(imputer, X_missing, y_missing):
  function get_full_score (line 135) | def get_full_score(X_full, y_full):
  function get_impute_zero_score (line 156) | def get_impute_zero_score(X_missing, y_missing):
  function get_impute_knn_score (line 182) | def get_impute_knn_score(X_missing, y_missing):
  function get_impute_mean (line 203) | def get_impute_mean(X_missing, y_missing):
  function get_impute_iterative (line 229) | def get_impute_iterative(X_missing, y_missing):

FILE: examples/linear_model/plot_ard.py
  function f (line 98) | def f(x, noise_amount):

FILE: examples/linear_model/plot_bayesian_ridge.py
  function f (line 93) | def f(x, noise_amount):

FILE: examples/linear_model/plot_bayesian_ridge_curvefit.py
  function func (line 37) | def func(x):

FILE: examples/linear_model/plot_lasso_model_selection.py
  function plot_ic_criterion (line 82) | def plot_ic_criterion(model, name, color):

FILE: examples/linear_model/plot_logistic_multinomial.py
  function plot_hyperplane (line 64) | def plot_hyperplane(c, color):

FILE: examples/linear_model/plot_ols_3d.py
  function plot_figs (line 38) | def plot_figs(fig_num, elev, azim, X_train, clf):

FILE: examples/linear_model/plot_poisson_regression_non_normal_loss.py
  function score_estimator (line 160) | def score_estimator(estimator, df_test):
  function _mean_frequency_by_risk_group (line 389) | def _mean_frequency_by_risk_group(y_true, y_pred, sample_weight=None, n_...
  function lorenz_curve (line 491) | def lorenz_curve(y_true, y_pred, exposure):

FILE: examples/linear_model/plot_polynomial_interpolation.py
  function f (line 58) | def f(x):
  function g (line 172) | def g(x):

FILE: examples/linear_model/plot_sgd_early_stopping.py
  function load_mnist (line 59) | def load_mnist(n_samples=None, class_0="0", class_1="8"):
  function fit_and_score (line 74) | def fit_and_score(estimator, max_iter, X_train, X_test, y_train, y_test):

FILE: examples/linear_model/plot_sgd_iris.py
  function plot_hyperplane (line 77) | def plot_hyperplane(c, color):

FILE: examples/linear_model/plot_sgd_loss_functions.py
  function modified_huber_loss (line 15) | def modified_huber_loss(y_true, y_pred):

FILE: examples/linear_model/plot_tweedie_regression_insurance_claims.py
  function load_mtpl2 (line 65) | def load_mtpl2(n_samples=100000):
  function plot_obs_pred (line 94) | def plot_obs_pred(
  function score_estimator (line 150) | def score_estimator(
  function lorenz_curve (line 573) | def lorenz_curve(y_true, y_pred, exposure):

FILE: examples/manifold/plot_lle_digits.py
  function plot_embedding (line 51) | def plot_embedding(X, title, ax):

FILE: examples/miscellaneous/plot_multilabel.py
  function plot_hyperplane (line 45) | def plot_hyperplane(clf, min_x, max_x, linestyle, label):
  function plot_subfigure (line 54) | def plot_subfigure(X, Y, subplot, title, transform):

FILE: examples/mixture/plot_concentration_prior.py
  function plot_ellipses (line 43) | def plot_ellipses(ax, weights, means, covars):
  function plot_results (line 61) | def plot_results(ax1, ax2, estimator, X, y, title, plot_title=False):

FILE: examples/mixture/plot_gmm.py
  function plot_results (line 39) | def plot_results(X, Y_, means, covariances, index, title):

FILE: examples/mixture/plot_gmm_covariances.py
  function make_ellipses (line 46) | def make_ellipses(gmm, ax):

FILE: examples/mixture/plot_gmm_sin.py
  function plot_results (line 54) | def plot_results(X, Y, means, covariances, index, title):
  function plot_samples (line 82) | def plot_samples(X, Y, n_components, index, title):

FILE: examples/model_selection/plot_cv_indices.py
  function visualize_groups (line 59) | def visualize_groups(classes, groups, name):
  function plot_cv_indices (line 98) | def plot_cv_indices(cv, X, y, group, ax, n_splits, lw=10):

FILE: examples/model_selection/plot_grid_search_refit_callable.py
  function lower_bound (line 33) | def lower_bound(cv_results):
  function best_low_complexity (line 57) | def best_low_complexity(cv_results):

FILE: examples/model_selection/plot_grid_search_stats.py
  function corrected_std (line 168) | def corrected_std(differences, n_train, n_test):
  function compute_corrected_ttest (line 193) | def compute_corrected_ttest(differences, df, n_train, n_test):

FILE: examples/model_selection/plot_learning_curve.py
  function plot_learning_curve (line 29) | def plot_learning_curve(

FILE: examples/model_selection/plot_randomized_search.py
  function report (line 41) | def report(results, n_top=3):

FILE: examples/model_selection/plot_successive_halving_heatmap.py
  function make_heatmap (line 55) | def make_heatmap(ax, gs, is_sh=False, make_cbar=False):

FILE: examples/model_selection/plot_underfitting_overfitting.py
  function true_fun (line 32) | def true_fun(X):

FILE: examples/neighbors/approximate_nearest_neighbors.py
  class NMSlibTransformer (line 72) | class NMSlibTransformer(TransformerMixin, BaseEstimator):
    method __init__ (line 75) | def __init__(self, n_neighbors=5, metric="euclidean", method="sw-graph...
    method fit (line 81) | def fit(self, X):
    method transform (line 98) | def transform(self, X):
  class AnnoyTransformer (line 118) | class AnnoyTransformer(TransformerMixin, BaseEstimator):
    method __init__ (line 121) | def __init__(self, n_neighbors=5, metric="euclidean", n_trees=10, sear...
    method fit (line 127) | def fit(self, X):
    method transform (line 135) | def transform(self, X):
    method fit_transform (line 138) | def fit_transform(self, X, y=None):
    method _transform (line 141) | def _transform(self, X):
  function test_transformers (line 175) | def test_transformers():
  function load_mnist (line 192) | def load_mnist(n_samples):
  function run_benchmark (line 199) | def run_benchmark():

FILE: examples/neighbors/plot_kde_1d.py
  function format_func (line 99) | def format_func(x, loc):

FILE: examples/neighbors/plot_nca_illustration.py
  function link_thickness_i (line 53) | def link_thickness_i(X, i):
  function relate_point (line 64) | def relate_point(X, i, ax):

FILE: examples/neighbors/plot_species_kde.py
  function construct_grids (line 58) | def construct_grids(batch):

FILE: examples/neural_networks/plot_mlp_training_curves.py
  function plot_on_dataset (line 92) | def plot_on_dataset(X, y, ax, name):

FILE: examples/neural_networks/plot_rbm_logistic_classification.py
  function nudge_dataset (line 48) | def nudge_dataset(X, Y):

FILE: examples/preprocessing/plot_all_scaling.py
  function create_axes (line 122) | def create_axes(title, figsize=(16, 6)):
  function plot_distribution (line 165) | def plot_distribution(axes, X, y, hist_nbins=50, title="", x0_label="", ...
  function make_plot (line 208) | def make_plot(item_idx):

FILE: examples/preprocessing/plot_discretization_classification.py
  function get_name (line 55) | def get_name(estimator):

FILE: examples/release_highlights/plot_release_highlights_0_22_0.py
  function test_sklearn_compatible_estimator (line 248) | def test_sklearn_compatible_estimator(estimator, check):

FILE: examples/semi_supervised/plot_semi_supervised_newsgroups.py
  function eval_and_print_metrics (line 66) | def eval_and_print_metrics(clf, X_train, y_train, X_test, y_test):

FILE: examples/svm/plot_custom_kernel.py
  function my_kernel (line 22) | def my_kernel(X, Y):

FILE: examples/svm/plot_iris_svc.py
  function make_meshgrid (line 42) | def make_meshgrid(x, y, h=0.02):
  function plot_contours (line 61) | def plot_contours(ax, clf, xx, yy, **params):

FILE: examples/svm/plot_rbf_parameters.py
  class MidpointNormalize (line 93) | class MidpointNormalize(Normalize):
    method __init__ (line 94) | def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
    method __call__ (line 98) | def __call__(self, value, clip=None):

FILE: examples/svm/plot_weighted_samples.py
  function plot_decision_function (line 22) | def plot_decision_function(classifier, sample_weight, axis, title):

FILE: examples/text/plot_document_classification_20newsgroups.py
  function is_interactive (line 101) | def is_interactive():
  function size_mb (line 154) | def size_mb(docs):
  function trim (line 213) | def trim(s):
  function benchmark (line 223) | def benchmark(clf):

FILE: examples/text/plot_document_clustering.py
  function is_interactive (line 125) | def is_interactive():

FILE: examples/text/plot_hashing_vs_dict_vectorizer.py
  function n_nonzero_columns (line 33) | def n_nonzero_columns(X):
  function tokens (line 38) | def tokens(doc):
  function token_freqs (line 47) | def token_freqs(doc):

FILE: maint_tools/create_issue_from_juint.py
  function get_issue (line 38) | def get_issue():
  function create_or_update_issue (line 48) | def create_or_update_issue(body):

FILE: maint_tools/sort_whats_new.py
  function entry_sort_key (line 12) | def entry_sort_key(s):

FILE: maint_tools/test_docstrings.py
  function get_all_methods (line 223) | def get_all_methods():
  function _is_checked_function (line 242) | def _is_checked_function(item):
  function get_all_functions_names (line 256) | def get_all_functions_names():
  function filter_errors (line 287) | def filter_errors(errors, method, Estimator=None):
  function repr_errors (line 326) | def repr_errors(res, estimator=None, method: Optional[str] = None) -> str:
  function test_function_docstring (line 382) | def test_function_docstring(function_name, request):
  function test_docstring (line 400) | def test_docstring(Estimator, method, request):

FILE: setup.py
  class CleanCommand (line 91) | class CleanCommand(Clean):
    method run (line 94) | def run(self):
  class build_ext_subclass (line 130) | class build_ext_subclass(build_ext):
    method finalize_options (line 131) | def finalize_options(self):
    method build_extensions (line 143) | def build_extensions(self):
  function configuration (line 177) | def configuration(parent_package="", top_path=None):
  function check_package_status (line 206) | def check_package_status(package, min_version):
  function setup_package (line 246) | def setup_package():

FILE: sklearn/__check_build/__init__.py
  function raise_build_error (line 16) | def raise_build_error(e):

FILE: sklearn/__check_build/setup.py
  function configuration (line 7) | def configuration(parent_package="", top_path=None):

FILE: sklearn/__init__.py
  function setup_module (line 132) | def setup_module(module):

FILE: sklearn/_build_utils/__init__.py
  function _check_cython_version (line 22) | def _check_cython_version():
  function cythonize_extensions (line 40) | def cythonize_extensions(top_path, config):
  function gen_from_templates (line 90) | def gen_from_templates(templates):

FILE: sklearn/_build_utils/openmp_helpers.py
  function get_openmp_flag (line 18) | def get_openmp_flag(compiler):
  function check_openmp_support (line 47) | def check_openmp_support():

FILE: sklearn/_build_utils/pre_build_helpers.py
  function _get_compiler (line 17) | def _get_compiler():
  function compile_test_program (line 46) | def compile_test_program(code, extra_preargs=[], extra_postargs=[]):
  function basic_check_build (line 100) | def basic_check_build():

FILE: sklearn/_config.py
  function _get_threadlocal_config (line 16) | def _get_threadlocal_config():
  function get_config (line 24) | def get_config():
  function set_config (line 42) | def set_config(
  function config_context (line 101) | def config_context(

FILE: sklearn/_loss/glm_distribution.py
  class ExponentialDispersionModel (line 19) | class ExponentialDispersionModel(metaclass=ABCMeta):
    method in_y_range (line 48) | def in_y_range(self, y):
    method unit_variance (line 69) | def unit_variance(self, y_pred):
    method unit_deviance (line 91) | def unit_deviance(self, y, y_pred, check_input=False):
    method unit_deviance_derivative (line 116) | def unit_deviance_derivative(self, y, y_pred):
    method deviance (line 134) | def deviance(self, y, y_pred, weights=1):
    method deviance_derivative (line 158) | def deviance_derivative(self, y, y_pred, weights=1):
  class TweedieDistribution (line 178) | class TweedieDistribution(ExponentialDispersionModel):
    method __init__ (line 204) | def __init__(self, power=0):
    method power (line 208) | def power(self):
    method power (line 212) | def power(self, power):
    method unit_variance (line 238) | def unit_variance(self, y_pred):
    method unit_deviance (line 249) | def unit_deviance(self, y, y_pred, check_input=False):
  class NormalDistribution (line 336) | class NormalDistribution(TweedieDistribution):
    method __init__ (line 339) | def __init__(self):
  class PoissonDistribution (line 343) | class PoissonDistribution(TweedieDistribution):
    method __init__ (line 346) | def __init__(self):
  class GammaDistribution (line 350) | class GammaDistribution(TweedieDistribution):
    method __init__ (line 353) | def __init__(self):
  class InverseGaussianDistribution (line 357) | class InverseGaussianDistribution(TweedieDistribution):
    method __init__ (line 360) | def __init__(self):

FILE: sklearn/_loss/tests/test_glm_distribution.py
  function test_family_bounds (line 33) | def test_family_bounds(family, expected):
  function test_invalid_distribution_bound (line 39) | def test_invalid_distribution_bound():
  function test_tweedie_distribution_power (line 46) | def test_tweedie_distribution_power():
  function test_deviance_zero (line 81) | def test_deviance_zero(family, chk_values):
  function test_deviance_derivative (line 102) | def test_deviance_derivative(family):

FILE: sklearn/base.py
  function clone (line 33) | def clone(estimator, *, safe=True):
  function _pprint (line 99) | def _pprint(params, offset=0, printer=repr):
  class BaseEstimator (line 149) | class BaseEstimator:
    method _get_param_names (line 160) | def _get_param_names(cls):
    method get_params (line 190) | def get_params(self, deep=True):
    method set_params (line 214) | def set_params(self, **params):
    method __repr__ (line 258) | def __repr__(self, N_CHAR_MAX=700):
    method __getstate__ (line 310) | def __getstate__(self):
    method __setstate__ (line 321) | def __setstate__(self, state):
    method _more_tags (line 341) | def _more_tags(self):
    method _get_tags (line 344) | def _get_tags(self):
    method _check_n_features (line 355) | def _check_n_features(self, X, reset):
    method _check_feature_names (line 401) | def _check_feature_names(self, X, *, reset):
    method _validate_data (line 491) | def _validate_data(
    method _repr_html_ (line 601) | def _repr_html_(self):
    method _repr_html_inner (line 616) | def _repr_html_inner(self):
    method _repr_mimebundle_ (line 623) | def _repr_mimebundle_(self, **kwargs):
  class ClassifierMixin (line 631) | class ClassifierMixin:
    method score (line 636) | def score(self, X, y, sample_weight=None):
    method _more_tags (line 664) | def _more_tags(self):
  class RegressorMixin (line 668) | class RegressorMixin:
    method score (line 673) | def score(self, X, y, sample_weight=None):
    method _more_tags (line 719) | def _more_tags(self):
  class ClusterMixin (line 723) | class ClusterMixin:
    method fit_predict (line 728) | def fit_predict(self, X, y=None):
    method _more_tags (line 750) | def _more_tags(self):
  class BiclusterMixin (line 754) | class BiclusterMixin:
    method biclusters_ (line 758) | def biclusters_(self):
    method get_indices (line 765) | def get_indices(self, i):
    method get_shape (line 786) | def get_shape(self, i):
    method get_submatrix (line 805) | def get_submatrix(self, i, data):
  class TransformerMixin (line 832) | class TransformerMixin:
    method fit_transform (line 835) | def fit_transform(self, X, y=None, **fit_params):
  class _OneToOneFeatureMixin (line 869) | class _OneToOneFeatureMixin:
    method get_feature_names_out (line 876) | def get_feature_names_out(self, input_features=None):
  class _ClassNamePrefixFeaturesOutMixin (line 898) | class _ClassNamePrefixFeaturesOutMixin:
    method get_feature_names_out (line 904) | def get_feature_names_out(self, input_features=None):
  class DensityMixin (line 923) | class DensityMixin:
    method score (line 928) | def score(self, X, y=None):
  class OutlierMixin (line 946) | class OutlierMixin:
    method fit_predict (line 951) | def fit_predict(self, X, y=None):
  class MetaEstimatorMixin (line 973) | class MetaEstimatorMixin:
  class MultiOutputMixin (line 978) | class MultiOutputMixin:
    method _more_tags (line 981) | def _more_tags(self):
  class _UnstableArchMixin (line 985) | class _UnstableArchMixin:
    method _more_tags (line 988) | def _more_tags(self):
  function is_classifier (line 996) | def is_classifier(estimator):
  function is_regressor (line 1012) | def is_regressor(estimator):
  function is_outlier_detector (line 1028) | def is_outlier_detector(estimator):
  function _is_pairwise (line 1044) | def _is_pairwise(estimator):

FILE: sklearn/calibration.py
  class CalibratedClassifierCV (line 53) | class CalibratedClassifierCV(ClassifierMixin, MetaEstimatorMixin, BaseEs...
    method __init__ (line 238) | def __init__(
    method fit (line 253) | def fit(self, X, y, sample_weight=None):
    method predict_proba (line 402) | def predict_proba(self, X):
    method predict (line 430) | def predict(self, X):
    method _more_tags (line 449) | def _more_tags(self):
  function _fit_classifier_calibrator_pair (line 461) | def _fit_classifier_calibrator_pair(
  function _get_prediction_method (line 527) | def _get_prediction_method(clf):
  function _compute_predictions (line 557) | def _compute_predictions(pred_method, method_name, X, n_classes):
  function _fit_calibrator (line 595) | def _fit_calibrator(clf, predictions, y, classes, method, sample_weight=...
  class _CalibratedClassifier (line 647) | class _CalibratedClassifier:
    method __init__ (line 670) | def __init__(self, base_estimator, calibrators, *, classes, method="si...
    method predict_proba (line 676) | def predict_proba(self, X):
  function _sigmoid_calibration (line 728) | def _sigmoid_calibration(predictions, y, sample_weight=None):
  class _SigmoidCalibration (line 798) | class _SigmoidCalibration(RegressorMixin, BaseEstimator):
    method fit (line 810) | def fit(self, X, y, sample_weight=None):
    method predict (line 836) | def predict(self, T):
  function calibration_curve (line 853) | def calibration_curve(
  class CalibrationDisplay (line 969) | class CalibrationDisplay:
    method __init__ (line 1043) | def __init__(
    method plot (line 1052) | def plot(self, *, ax=None, name=None, ref_line=True, **kwargs):
    method from_estimator (line 1114) | def from_estimator(
    method from_predictions (line 1240) | def from_predictions(

FILE: sklearn/cluster/_affinity_propagation.py
  function _equal_similarities_and_preferences (line 24) | def _equal_similarities_and_preferences(S, preference):
  function affinity_propagation (line 38) | def affinity_propagation(
  class AffinityPropagation (line 267) | class AffinityPropagation(ClusterMixin, BaseEstimator):
    method __init__ (line 397) | def __init__(
    method _pairwise (line 426) | def _pairwise(self):
    method _more_tags (line 429) | def _more_tags(self):
    method fit (line 432) | def fit(self, X, y=None):
    method predict (line 503) | def predict(self, X):
    method fit_predict (line 536) | def fit_predict(self, X, y=None):

FILE: sklearn/cluster/_agglomerative.py
  function _fix_connectivity (line 35) | def _fix_connectivity(X, connectivity, affinity):
  function _single_linkage_tree (line 110) | def _single_linkage_tree(
  function ward_tree (line 170) | def ward_tree(X, *, connectivity=None, n_clusters=None, return_distance=...
  function linkage_tree (line 385) | def linkage_tree(
  function _complete_linkage (line 663) | def _complete_linkage(*args, **kwargs):
  function _average_linkage (line 668) | def _average_linkage(*args, **kwargs):
  function _single_linkage (line 673) | def _single_linkage(*args, **kwargs):
  function _hc_cut (line 689) | def _hc_cut(n_clusters, children, n_leaves):
  class AgglomerativeClustering (line 740) | class AgglomerativeClustering(ClusterMixin, BaseEstimator):
    method __init__ (line 878) | def __init__(
    method fit (line 899) | def fit(self, X, y=None):
    method _fit (line 920) | def _fit(self, X):
    method fit_predict (line 1033) | def fit_predict(self, X, y=None):
  class FeatureAgglomeration (line 1057) | class FeatureAgglomeration(AgglomerativeClustering, AgglomerationTransfo...
    method __init__ (line 1196) | def __init__(
    method fit (line 1221) | def fit(self, X, y=None):
    method fit_predict (line 1242) | def fit_predict(self):

FILE: sklearn/cluster/_bicluster.py
  function _scale_normalize (line 25) | def _scale_normalize(X):
  function _bistochastic_normalize (line 46) | def _bistochastic_normalize(X, max_iter=1000, tol=1e-5):
  function _log_normalize (line 67) | def _log_normalize(X):
  class BaseSpectral (line 83) | class BaseSpectral(BiclusterMixin, BaseEstimator, metaclass=ABCMeta):
    method __init__ (line 87) | def __init__(
    method _check_parameters (line 105) | def _check_parameters(self):
    method fit (line 114) | def fit(self, X, y=None):
    method _svd (line 135) | def _svd(self, array, n_components, n_discard):
    method _k_means (line 172) | def _k_means(self, data, n_clusters):
    method _more_tags (line 192) | def _more_tags(self):
  class SpectralCoclustering (line 206) | class SpectralCoclustering(BaseSpectral):
    method __init__ (line 316) | def __init__(
    method _fit (line 331) | def _fit(self, X):
  class SpectralBiclustering (line 349) | class SpectralBiclustering(BaseSpectral):
    method __init__ (line 474) | def __init__(
    method _check_parameters (line 495) | def _check_parameters(self):
    method _fit (line 536) | def _fit(self, X):
    method _fit_best_piecewise (line 579) | def _fit_best_piecewise(self, vectors, n_best, n_clusters):
    method _project_and_cluster (line 597) | def _project_and_cluster(self, data, vectors, n_clusters):

FILE: sklearn/cluster/_birch.py
  function _iterate_sparse_X (line 23) | def _iterate_sparse_X(X):
  function _split_node (line 41) | def _split_node(node, threshold, branching_factor):
  class _CFNode (line 97) | class _CFNode:
    method __init__ (line 145) | def __init__(self, *, threshold, branching_factor, is_leaf, n_features):
    method append_subcluster (line 160) | def append_subcluster(self, subcluster):
    method update_split_subclusters (line 172) | def update_split_subclusters(self, subcluster, new_subcluster1, new_su...
    method insert_cf_subcluster (line 182) | def insert_cf_subcluster(self, subcluster):
  class _CFSubcluster (line 250) | class _CFSubcluster:
    method __init__ (line 286) | def __init__(self, *, linear_sum=None):
    method update (line 299) | def update(self, subcluster):
    method merge_subcluster (line 306) | def merge_subcluster(self, nominee_cluster, threshold):
    method radius (line 338) | def radius(self):
  class Birch (line 345) | class Birch(ClusterMixin, TransformerMixin, BaseEstimator):
    method __init__ (line 465) | def __init__(
    method fit_ (line 486) | def fit_(self):
    method partial_fit_ (line 495) | def partial_fit_(self):
    method fit (line 498) | def fit(self, X, y=None):
    method _fit (line 543) | def _fit(self, X, partial):
    method _get_leaves (line 606) | def _get_leaves(self):
    method partial_fit (line 622) | def partial_fit(self, X=None, y=None):
    method _check_fit (line 650) | def _check_fit(self, X):
    method predict (line 661) | def predict(self, X):
    method transform (line 687) | def transform(self, X):
    method _global_clustering (line 709) | def _global_clustering(self, X=None):

FILE: sklearn/cluster/_dbscan.py
  function dbscan (line 25) | def dbscan(
  class DBSCAN (line 166) | class DBSCAN(ClusterMixin, BaseEstimator):
    method __init__ (line 302) | def __init__(
    method fit (line 323) | def fit(self, X, y=None, sample_weight=None):
    method fit_predict (line 434) | def fit_predict(self, X, y=None, sample_weight=None):

FILE: sklearn/cluster/_feature_agglomeration.py
  class AgglomerationTransform (line 18) | class AgglomerationTransform(TransformerMixin):
    method transform (line 23) | def transform(self, X):
    method inverse_transform (line 57) | def inverse_transform(self, Xred):

FILE: sklearn/cluster/_kmeans.py
  function kmeans_plusplus (line 52) | def kmeans_plusplus(
  function _kmeans_plusplus (line 148) | def _kmeans_plusplus(X, n_clusters, x_squared_norms, random_state, n_loc...
  function _tolerance (line 246) | def _tolerance(X, tol):
  function k_means (line 257) | def k_means(
  function _kmeans_single_elkan (line 383) | def _kmeans_single_elkan(
  function _kmeans_single_lloyd (line 544) | def _kmeans_single_lloyd(
  function _labels_inertia (line 684) | def _labels_inertia(X, sample_weight, x_squared_norms, centers, n_thread...
  function _labels_inertia_threadpool_limit (line 751) | def _labels_inertia_threadpool_limit(
  class KMeans (line 763) | class KMeans(TransformerMixin, ClusterMixin, BaseEstimator):
    method __init__ (line 911) | def __init__(
    method _check_params (line 935) | def _check_params(self, X):
    method _validate_center_shape (line 993) | def _validate_center_shape(self, X, centers):
    method _check_test_data (line 1006) | def _check_test_data(self, X):
    method _check_mkl_vcomp (line 1017) | def _check_mkl_vcomp(self, X, n_samples):
    method _init_centroids (line 1052) | def _init_centroids(self, X, x_squared_norms, init, random_state, init...
    method fit (line 1111) | def fit(self, X, y=None, sample_weight=None):
    method fit_predict (line 1232) | def fit_predict(self, X, y=None, sample_weight=None):
    method fit_transform (line 1257) | def fit_transform(self, X, y=None, sample_weight=None):
    method transform (line 1281) | def transform(self, X):
    method _transform (line 1303) | def _transform(self, X):
    method predict (line 1307) | def predict(self, X, sample_weight=None):
    method score (line 1338) | def score(self, X, y=None, sample_weight=None):
    method _more_tags (line 1368) | def _more_tags(self):
  function _mini_batch_step (line 1378) | def _mini_batch_step(
  class MiniBatchKMeans (line 1502) | class MiniBatchKMeans(KMeans):
    method __init__ (line 1687) | def __init__(
    method counts_ (line 1725) | def counts_(self):
    method init_size_ (line 1733) | def init_size_(self):
    method random_state_ (line 1741) | def random_state_(self):
    method _check_params (line 1744) | def _check_params(self, X):
    method _mini_batch_convergence (line 1787) | def _mini_batch_convergence(
    method _random_reassign (line 1852) | def _random_reassign(self):
    method fit (line 1868) | def fit(self, X, y=None, sample_weight=None):
    method partial_fit (line 2024) | def partial_fit(self, X, y=None, sample_weight=None):
    method predict (line 2124) | def predict(self, X, sample_weight=None):
    method _more_tags (line 2161) | def _more_tags(self):

FILE: sklearn/cluster/_mean_shift.py
  function estimate_bandwidth (line 31) | def estimate_bandwidth(X, *, quantile=0.3, n_samples=None, random_state=...
  function _mean_shift_single_seed (line 87) | def _mean_shift_single_seed(my_mean, X, nbrs, max_iter):
  function mean_shift (line 110) | def mean_shift(
  function get_bin_seeds (line 203) | def get_bin_seeds(X, bin_size, min_bin_freq=1):
  class MeanShift (line 256) | class MeanShift(ClusterMixin, BaseEstimator):
    method __init__ (line 383) | def __init__(
    method fit (line 402) | def fit(self, X, y=None):
    method predict (line 499) | def predict(self, X):

FILE: sklearn/cluster/_optics.py
  class OPTICS (line 26) | class OPTICS(ClusterMixin, BaseEstimator):
    method __init__ (line 224) | def __init__(
    method fit (line 257) | def fit(self, X, y=None):
  function _validate_size (line 348) | def _validate_size(size, n_samples, param_name):
  function _compute_core_distances_ (line 362) | def _compute_core_distances_(X, neighbors, min_samples, working_memory):
  function compute_optics_graph (line 398) | def compute_optics_graph(
  function _set_reach_dist (line 578) | def _set_reach_dist(
  function cluster_optics_dbscan (line 623) | def cluster_optics_dbscan(*, reachability, core_distances, ordering, eps):
  function cluster_optics_xi (line 661) | def cluster_optics_xi(
  function _extend_region (line 741) | def _extend_region(steep_point, xward_point, start, min_samples):
  function _update_filter_sdas (line 804) | def _update_filter_sdas(sdas, mib, xi_complement, reachability_plot):
  function _correct_predecessor (line 818) | def _correct_predecessor(reachability_plot, predecessor_plot, ordering, ...
  function _xi_cluster (line 840) | def _xi_cluster(
  function _extract_xi_labels (line 995) | def _extract_xi_labels(ordering, clusters):

FILE: sklearn/cluster/_spectral.py
  function cluster_qr (line 25) | def cluster_qr(vectors):
  function discretize (line 57) | def discretize(
  function spectral_clustering (line 193) | def spectral_clustering(
  class SpectralClustering (line 379) | class SpectralClustering(ClusterMixin, BaseEstimator):
    method __init__ (line 590) | def __init__(
    method fit (line 625) | def fit(self, X, y=None):
    method fit_predict (line 704) | def fit_predict(self, X, y=None):
    method _more_tags (line 728) | def _more_tags(self):
    method _pairwise (line 741) | def _pairwise(self):

FILE: sklearn/cluster/setup.py
  function configuration (line 8) | def configuration(parent_package="", top_path=None):

FILE: sklearn/cluster/tests/common.py
  function generate_clustered_data (line 13) | def generate_clustered_data(

FILE: sklearn/cluster/tests/test_affinity_propagation.py
  function test_affinity_propagation (line 31) | def test_affinity_propagation():
  function test_affinity_propagation_affinity_shape (line 68) | def test_affinity_propagation_affinity_shape():
  function test_affinity_propagation_params_validation (line 92) | def test_affinity_propagation_params_validation(input, params, err_type,...
  function test_affinity_propagation_predict (line 98) | def test_affinity_propagation_predict():
  function test_affinity_propagation_predict_error (line 106) | def test_affinity_propagation_predict_error():
  function test_affinity_propagation_fit_non_convergence (line 121) | def test_affinity_propagation_fit_non_convergence():
  function test_affinity_propagation_equal_mutual_similarities (line 136) | def test_affinity_propagation_equal_mutual_similarities():
  function test_affinity_propagation_predict_non_convergence (line 168) | def test_affinity_propagation_predict_non_convergence():
  function test_affinity_propagation_non_convergence_regressiontest (line 185) | def test_affinity_propagation_non_convergence_regressiontest():
  function test_equal_similarities_and_preferences (line 191) | def test_equal_similarities_and_preferences():
  function test_affinity_propagation_random_state (line 212) | def test_affinity_propagation_random_state():
  function test_affinity_propagation_convergence_warning_dense_sparse (line 233) | def test_affinity_propagation_convergence_warning_dense_sparse(centers):
  function test_affinity_propagation_float32 (line 246) | def test_affinity_propagation_float32():
  function test_sparse_input_for_predict (line 259) | def test_sparse_input_for_predict():
  function test_sparse_input_for_fit_predict (line 268) | def test_sparse_input_for_fit_predict():
  function test_affinity_propagation_pairwise_is_deprecated (line 279) | def test_affinity_propagation_pairwise_is_deprecated():

FILE: sklearn/cluster/tests/test_bicluster.py
  class MockBiclustering (line 26) | class MockBiclustering(BiclusterMixin, BaseEstimator):
    method __init__ (line 28) | def __init__(self):
    method get_indices (line 31) | def get_indices(self, i):
  function test_get_submatrix (line 39) | def test_get_submatrix():
  function _test_shape_indices (line 54) | def _test_shape_indices(model):
  function test_spectral_coclustering (line 63) | def test_spectral_coclustering():
  function test_spectral_biclustering (line 91) | def test_spectral_biclustering():
  function _do_scale_test (line 131) | def _do_scale_test(scaled):
  function _do_bistochastic_test (line 142) | def _do_bistochastic_test(scaled):
  function test_scale_normalize (line 148) | def test_scale_normalize():
  function test_bistochastic_normalize (line 158) | def test_bistochastic_normalize():
  function test_log_normalize (line 168) | def test_log_normalize():
  function test_fit_best_piecewise (line 177) | def test_fit_best_piecewise():
  function test_project_and_cluster (line 184) | def test_project_and_cluster():
  function test_perfect_checkerboard (line 193) | def test_perfect_checkerboard():
  function test_errors (line 223) | def test_errors(args):
  function test_wrong_shape (line 231) | def test_wrong_shape():
  function test_n_features_in_ (line 239) | def test_n_features_in_(est):

FILE: sklearn/cluster/tests/test_birch.py
  function test_n_samples_leaves_roots (line 22) | def test_n_samples_leaves_roots():
  function test_partial_fit (line 35) | def test_partial_fit():
  function test_birch_predict (line 52) | def test_birch_predict():
  function test_n_clusters (line 69) | def test_n_clusters():
  function test_sparse_X (line 98) | def test_sparse_X():
  function test_partial_fit_second_call_error_checks (line 112) | def test_partial_fit_second_call_error_checks():
  function check_branching_factor (line 124) | def check_branching_factor(node, branching_factor):
  function test_branching_factor (line 132) | def test_branching_factor():
  function check_threshold (line 146) | def check_threshold(birch_instance, threshold):
  function test_threshold (line 156) | def test_threshold():
  function test_birch_n_clusters_long_int (line 168) | def test_birch_n_clusters_long_int():
  function test_birch_fit_attributes_deprecated (line 178) | def test_birch_fit_attributes_deprecated(attribute):
  function test_birch_params_validation (line 217) | def test_birch_params_validation(params, err_type, err_msg):

FILE: sklearn/cluster/tests/test_dbscan.py
  function test_dbscan_similarity (line 28) | def test_dbscan_similarity():
  function test_dbscan_feature (line 52) | def test_dbscan_feature():
  function test_dbscan_sparse (line 74) | def test_dbscan_sparse():
  function test_dbscan_sparse_precomputed (line 82) | def test_dbscan_sparse_precomputed(include_self):
  function test_dbscan_sparse_precomputed_different_eps (line 97) | def test_dbscan_sparse_precomputed_different_eps():
  function test_dbscan_input_not_modified (line 116) | def test_dbscan_input_not_modified(use_sparse, metric):
  function test_dbscan_no_core_samples (line 129) | def test_dbscan_no_core_samples():
  function test_dbscan_callable (line 141) | def test_dbscan_callable():
  function test_dbscan_metric_params (line 166) | def test_dbscan_metric_params():
  function test_dbscan_balltree (line 227) | def test_dbscan_balltree():
  function test_input_validation (line 266) | def test_input_validation():
  function test_dbscan_badargs (line 279) | def test_dbscan_badargs(args):
  function test_pickle (line 285) | def test_pickle():
  function test_boundaries (line 291) | def test_boundaries():
  function test_weighted_dbscan (line 302) | def test_weighted_dbscan():
  function test_dbscan_core_samples_toy (line 371) | def test_dbscan_core_samples_toy(algorithm):
  function test_dbscan_precomputed_metric_with_degenerate_input_arrays (line 400) | def test_dbscan_precomputed_metric_with_degenerate_input_arrays():
  function test_dbscan_precomputed_metric_with_initial_rows_zero (line 412) | def test_dbscan_precomputed_metric_with_initial_rows_zero():
  function test_dbscan_params_validation (line 460) | def test_dbscan_params_validation(params, err_type, err_msg):

FILE: sklearn/cluster/tests/test_feature_agglomeration.py
  function test_feature_agglomeration (line 11) | def test_feature_agglomeration():

FILE: sklearn/cluster/tests/test_hierarchical.py
  function test_linkage_misc (line 53) | def test_linkage_misc():
  function test_structured_linkage_tree (line 80) | def test_structured_linkage_tree():
  function test_unstructured_linkage_tree (line 103) | def test_unstructured_linkage_tree():
  function test_height_linkage_tree (line 127) | def test_height_linkage_tree():
  function test_agglomerative_clustering_wrong_arg_memory (line 141) | def test_agglomerative_clustering_wrong_arg_memory():
  function test_zero_cosine_linkage_tree (line 153) | def test_zero_cosine_linkage_tree():
  function test_agglomerative_clustering_distances (line 165) | def test_agglomerative_clustering_distances(
  function test_agglomerative_clustering (line 193) | def test_agglomerative_clustering():
  function test_agglomerative_clustering_memory_mapped (line 287) | def test_agglomerative_clustering_memory_mapped():
  function test_ward_agglomeration (line 297) | def test_ward_agglomeration():
  function test_single_linkage_clustering (line 318) | def test_single_linkage_clustering():
  function assess_same_labelling (line 335) | def assess_same_labelling(cut1, cut2):
  function test_sparse_scikit_vs_scipy (line 347) | def test_sparse_scikit_vs_scipy():
  function test_vector_scikit_single_vs_scipy_single (line 388) | def test_vector_scikit_single_vs_scipy_single(seed):
  function test_mst_linkage_core_memory_mapped (line 414) | def test_mst_linkage_core_memory_mapped(metric):
  function test_identical_points (line 432) | def test_identical_points():
  function test_connectivity_propagation (line 452) | def test_connectivity_propagation():
  function test_ward_tree_children_order (line 483) | def test_ward_tree_children_order():
  function test_ward_linkage_tree_return_distance (line 503) | def test_ward_linkage_tree_return_distance():
  function test_connectivity_fixing_non_lil (line 621) | def test_connectivity_fixing_non_lil():
  function test_int_float_dict (line 634) | def test_int_float_dict():
  function test_connectivity_callable (line 651) | def test_connectivity_callable():
  function test_connectivity_ignores_diagonal (line 664) | def test_connectivity_ignores_diagonal():
  function test_compute_full_tree (line 676) | def test_compute_full_tree():
  function test_n_components (line 702) | def test_n_components():
  function test_agg_n_clusters (line 714) | def test_agg_n_clusters():
  function test_affinity_passed_to_fix_connectivity (line 728) | def test_affinity_passed_to_fix_connectivity():
  function test_agglomerative_clustering_with_distance_threshold (line 755) | def test_agglomerative_clustering_with_distance_threshold(linkage):
  function test_small_distance_threshold (line 793) | def test_small_distance_threshold():
  function test_cluster_distances_with_distance_threshold (line 810) | def test_cluster_distances_with_distance_threshold():
  function test_agglomerative_clustering_with_distance_threshold_edge_case (line 841) | def test_agglomerative_clustering_with_distance_threshold_edge_case(
  function test_dist_threshold_invalid_parameters (line 853) | def test_dist_threshold_invalid_parameters():
  function test_invalid_shape_precomputed_dist_matrix (line 868) | def test_invalid_shape_precomputed_dist_matrix():
  function test_precomputed_connectivity_affinity_with_2_connected_components (line 877) | def test_precomputed_connectivity_affinity_with_2_connected_components():

FILE: sklearn/cluster/tests/test_k_means.py
  function test_kmeans_results (line 57) | def test_kmeans_results(array_constr, algo, dtype):
  function test_kmeans_relocated_clusters (line 82) | def test_kmeans_relocated_clusters(array_constr, algo):
  function test_relocate_empty_clusters (line 106) | def test_relocate_empty_clusters(array_constr):
  function test_kmeans_elkan_results (line 152) | def test_kmeans_elkan_results(distribution, array_constr, tol):
  function test_kmeans_convergence (line 176) | def test_kmeans_convergence(algorithm):
  function test_minibatch_update_consistency (line 194) | def test_minibatch_update_consistency():
  function _check_fitted_model (line 266) | def _check_fitted_model(km):
  function test_all_init (line 287) | def test_all_init(Estimator, data, init):
  function test_minibatch_kmeans_partial_fit_init (line 301) | def test_minibatch_kmeans_partial_fit_init(init):
  function test_fortran_aligned_data (line 314) | def test_fortran_aligned_data(Estimator):
  function test_k_means_fit_predict (line 341) | def test_k_means_fit_predict(algo, dtype, constructor, seed, max_iter, t...
  function test_minibatch_kmeans_verbose (line 359) | def test_minibatch_kmeans_verbose():
  function test_kmeans_verbose (line 372) | def test_kmeans_verbose(algorithm, tol, capsys):
  function test_minibatch_kmeans_warning_init_size (line 397) | def test_minibatch_kmeans_warning_init_size():
  function test_warning_n_init_precomputed_centers (line 406) | def test_warning_n_init_precomputed_centers(Estimator):
  function test_minibatch_sensible_reassign (line 416) | def test_minibatch_sensible_reassign():
  function test_minibatch_reassign (line 445) | def test_minibatch_reassign(data):
  function test_minibatch_with_many_reassignments (line 498) | def test_minibatch_with_many_reassignments():
  function test_minibatch_kmeans_init_size (line 512) | def test_minibatch_kmeans_init_size():
  function test_minibatch_declared_convergence (line 531) | def test_minibatch_declared_convergence(capsys, tol, max_no_improvement):
  function test_minibatch_iter_steps (line 558) | def test_minibatch_iter_steps():
  function test_kmeans_copyx (line 583) | def test_kmeans_copyx():
  function test_score_max_iter (line 595) | def test_score_max_iter(Estimator):
  function test_predict (line 616) | def test_predict(Estimator, algorithm, init, dtype, array_constr):
  function test_dense_sparse (line 642) | def test_dense_sparse(Estimator):
  function test_predict_dense_sparse (line 658) | def test_predict_dense_sparse(Estimator, init):
  function test_integer_input (line 677) | def test_integer_input(Estimator, array_constr, dtype, init):
  function test_transform (line 704) | def test_transform(Estimator):
  function test_fit_transform (line 722) | def test_fit_transform(Estimator):
  function test_n_init (line 729) | def test_n_init():
  function test_k_means_function (line 745) | def test_k_means_function():
  function test_float_precision (line 761) | def test_float_precision(Estimator, data):
  function test_centers_not_mutated (line 797) | def test_centers_not_mutated(Estimator, dtype):
  function test_kmeans_init_fitted_centers (line 811) | def test_kmeans_init_fitted_centers(data):
  function test_kmeans_warns_less_centers_than_unique_points (line 820) | def test_kmeans_warns_less_centers_than_unique_points():
  function _sort_centers (line 837) | def _sort_centers(centers):
  function test_weighted_vs_repeated (line 841) | def test_weighted_vs_repeated():
  function test_unit_weights_vs_no_weights (line 865) | def test_unit_weights_vs_no_weights(Estimator, data):
  function test_scaled_weights (line 880) | def test_scaled_weights(Estimator, data):
  function test_kmeans_elkan_iter_attribute (line 893) | def test_kmeans_elkan_iter_attribute():
  function test_kmeans_empty_cluster_relocated (line 903) | def test_kmeans_empty_cluster_relocated(array_constr):
  function test_result_equal_in_diff_n_threads (line 918) | def test_result_equal_in_diff_n_threads(Estimator):
  function test_minibatch_kmeans_deprecated_attributes (line 932) | def test_minibatch_kmeans_deprecated_attributes(attr):
  function test_warning_elkan_1_cluster (line 945) | def test_warning_elkan_1_cluster():
  function test_k_means_1_iteration (line 958) | def test_k_means_1_iteration(array_constr, algo):
  function test_euclidean_distance (line 987) | def test_euclidean_distance(dtype, squared):
  function test_inertia (line 1012) | def test_inertia(dtype):
  function test_sample_weight_unchanged (line 1037) | def test_sample_weight_unchanged(Estimator):
  function test_wrong_params (line 1080) | def test_wrong_params(Estimator, param, match):
  function test_kmeans_wrong_params (line 1093) | def test_kmeans_wrong_params(param, match):
  function test_minibatch_kmeans_wrong_params (line 1109) | def test_minibatch_kmeans_wrong_params(param, match):
  function test_kmeans_plusplus_wrong_params (line 1131) | def test_kmeans_plusplus_wrong_params(param, match):
  function test_kmeans_plusplus_output (line 1138) | def test_kmeans_plusplus_output(data, dtype):
  function test_kmeans_plusplus_norms (line 1161) | def test_kmeans_plusplus_norms(x_squared_norms):
  function test_kmeans_plusplus_dataorder (line 1168) | def test_kmeans_plusplus_dataorder():
  function test_is_same_clustering (line 1179) | def test_is_same_clustering():

FILE: sklearn/cluster/tests/test_mean_shift.py
  function test_estimate_bandwidth (line 36) | def test_estimate_bandwidth():
  function test_estimate_bandwidth_1sample (line 42) | def test_estimate_bandwidth_1sample():
  function test_mean_shift (line 53) | def test_mean_shift(bandwidth, cluster_all, expected, first_cluster_label):
  function test_mean_shift_negative_bandwidth (line 69) | def test_mean_shift_negative_bandwidth():
  function test_estimate_bandwidth_with_sparse_matrix (line 77) | def test_estimate_bandwidth_with_sparse_matrix():
  function test_parallel (line 85) | def test_parallel():
  function test_meanshift_predict (line 106) | def test_meanshift_predict():
  function test_meanshift_all_orphans (line 114) | def test_meanshift_all_orphans():
  function test_unfitted (line 124) | def test_unfitted():
  function test_cluster_intensity_tie (line 131) | def test_cluster_intensity_tie():
  function test_bin_seeds (line 141) | def test_bin_seeds():
  function test_max_iter (line 182) | def test_max_iter(max_iter):
  function test_mean_shift_zero_bandwidth (line 194) | def test_mean_shift_zero_bandwidth():

FILE: sklearn/cluster/tests/test_optics.py
  function test_extend_downward (line 41) | def test_extend_downward(r_plot, end):
  function test_extend_upward (line 60) | def test_extend_upward(r_plot, end):
  function test_the_extract_xi_labels (line 79) | def test_the_extract_xi_labels(ordering, clusters, expected):
  function test_extract_xi (line 85) | def test_extract_xi():
  function test_cluster_hierarchy_ (line 138) | def test_cluster_hierarchy_():
  function test_correct_number_of_clusters (line 152) | def test_correct_number_of_clusters():
  function test_minimum_number_of_sample_check (line 180) | def test_minimum_number_of_sample_check():
  function test_bad_extract (line 193) | def test_bad_extract():
  function test_bad_reachability (line 207) | def test_bad_reachability():
  function test_nowarn_if_metric_bool_data_bool (line 219) | def test_nowarn_if_metric_bool_data_bool():
  function test_warn_if_metric_bool_data_no_bool (line 232) | def test_warn_if_metric_bool_data_no_bool():
  function test_nowarn_if_metric_no_bool (line 247) | def test_nowarn_if_metric_no_bool():
  function test_close_extract (line 262) | def test_close_extract():
  function test_dbscan_optics_parity (line 278) | def test_dbscan_optics_parity(eps, min_samples):
  function test_min_samples_edge_case (line 304) | def test_min_samples_edge_case():
  function test_min_cluster_size (line 326) | def test_min_cluster_size(min_cluster_size):
  function test_min_cluster_size_invalid (line 341) | def test_min_cluster_size_invalid(min_cluster_size):
  function test_min_cluster_size_invalid2 (line 347) | def test_min_cluster_size_invalid2():
  function test_processing_order (line 353) | def test_processing_order():
  function test_compare_to_ELKI (line 363) | def test_compare_to_ELKI():
  function test_wrong_cluster_method (line 765) | def test_wrong_cluster_method():
  function test_extract_dbscan (line 771) | def test_extract_dbscan():
  function test_precomputed_dists (line 786) | def test_precomputed_dists():

FILE: sklearn/cluster/tests/test_spectral.py
  function test_spectral_clustering (line 34) | def test_spectral_clustering(eigen_solver, assign_labels):
  function test_spectral_unknown_mode (line 67) | def test_spectral_unknown_mode():
  function test_spectral_unknown_assign_labels (line 86) | def test_spectral_unknown_assign_labels():
  function test_spectral_clustering_sparse (line 106) | def test_spectral_clustering_sparse(assign_labels):
  function test_precomputed_nearest_neighbors_filtering (line 128) | def test_precomputed_nearest_neighbors_filtering():
  function test_affinities (line 154) | def test_affinities():
  function test_cluster_qr (line 201) | def test_cluster_qr():
  function test_cluster_qr_permutation_invariance (line 219) | def test_cluster_qr_permutation_invariance():
  function test_discretize (line 232) | def test_discretize(n_samples):
  function test_spectral_clustering_with_arpack_amg_solvers (line 264) | def test_spectral_clustering_with_arpack_amg_solvers():
  function test_n_components (line 300) | def test_n_components():
  function test_verbose (line 324) | def test_verbose(assign_labels, capsys):
  function test_pairwise_is_deprecated (line 343) | def test_pairwise_is_deprecated(affinity):
  function test_spectral_clustering_np_matrix_raises (line 350) | def test_spectral_clustering_np_matrix_raises():
  function test_spectral_clustering_not_infinite_loop (line 360) | def test_spectral_clustering_not_infinite_loop(capsys, monkeypatch):

FILE: sklearn/compose/_column_transformer.py
  class ColumnTransformer (line 40) | class ColumnTransformer(TransformerMixin, _BaseComposition):
    method __init__ (line 198) | def __init__(
    method _transformers (line 218) | def _transformers(self):
    method _transformers (line 228) | def _transformers(self, value):
    method get_params (line 234) | def get_params(self, deep=True):
    method set_params (line 254) | def set_params(self, **kwargs):
    method _iter (line 274) | def _iter(self, fitted=False, replace_strings=False, column_as_strings...
    method _validate_transformers (line 320) | def _validate_transformers(self):
    method _validate_column_callables (line 342) | def _validate_column_callables(self, X):
    method _validate_remainder (line 357) | def _validate_remainder(self, X):
    method named_transformers_ (line 379) | def named_transformers_(self):
    method get_feature_names (line 393) | def get_feature_names(self):
    method _get_feature_name_out_for_transformer (line 426) | def _get_feature_name_out_for_transformer(
    method get_feature_names_out (line 456) | def get_feature_names_out(self, input_features=None):
    method _update_fitted_transformers (line 527) | def _update_fitted_transformers(self, transformers):
    method _validate_output (line 550) | def _validate_output(self, result):
    method _record_output_indices (line 565) | def _record_output_indices(self, Xs):
    method _log_message (line 587) | def _log_message(self, name, idx, total):
    method _fit_transform (line 592) | def _fit_transform(self, X, y, func, fitted=False, column_as_strings=F...
    method fit (line 623) | def fit(self, X, y=None):
    method fit_transform (line 645) | def fit_transform(self, X, y=None):
    method transform (line 701) | def transform(self, X):
    method _hstack (line 763) | def _hstack(self, Xs):
    method _sk_visual_block_ (line 793) | def _sk_visual_block_(self):
  function _check_X (line 816) | def _check_X(X):
  function _is_empty_column_selection (line 823) | def _is_empty_column_selection(column):
  function _get_transformer_list (line 841) | def _get_transformer_list(estimators):
  function make_column_transformer (line 853) | def make_column_transformer(
  class make_column_selector (line 966) | class make_column_selector:
    method __init__ (line 1021) | def __init__(self, pattern=None, *, dtype_include=None, dtype_exclude=...
    method __call__ (line 1026) | def __call__(self, df):

FILE: sklearn/compose/_target.py
  class TransformedTargetRegressor (line 19) | class TransformedTargetRegressor(RegressorMixin, BaseEstimator):
    method __init__ (line 130) | def __init__(
    method _fit_transformer (line 145) | def _fit_transformer(self, y):
    method fit (line 189) | def fit(self, X, y, **fit_params):
    method predict (line 254) | def predict(self, X, **predict_params):
    method _more_tags (line 289) | def _more_tags(self):
    method n_features_in_ (line 302) | def n_features_in_(self):

FILE: sklearn/compose/tests/test_column_transformer.py
  class Trans (line 28) | class Trans(BaseEstimator):
    method fit (line 29) | def fit(self, X, y=None):
    method transform (line 32) | def transform(self, X, y=None):
  class DoubleTrans (line 42) | class DoubleTrans(BaseEstimator):
    method fit (line 43) | def fit(self, X, y=None):
    method transform (line 46) | def transform(self, X):
  class SparseMatrixTrans (line 50) | class SparseMatrixTrans(BaseEstimator):
    method fit (line 51) | def fit(self, X, y=None):
    method transform (line 54) | def transform(self, X, y=None):
  class TransNo2D (line 59) | class TransNo2D(BaseEstimator):
    method fit (line 60) | def fit(self, X, y=None):
    method transform (line 63) | def transform(self, X, y=None):
  class TransRaise (line 67) | class TransRaise(BaseEstimator):
    method fit (line 68) | def fit(self, X, y=None):
    method transform (line 71) | def transform(self, X, y=None):
  function test_column_transformer (line 75) | def test_column_transformer():
  function test_column_transformer_dataframe (line 141) | def test_column_transformer_dataframe():
  function test_column_transformer_empty_columns (line 272) | def test_column_transformer_empty_columns(pandas, column_selection, call...
  function test_column_transformer_output_indices (line 319) | def test_column_transformer_output_indices():
  function test_column_transformer_output_indices_df (line 362) | def test_column_transformer_output_indices_df():
  function test_column_transformer_sparse_array (line 393) | def test_column_transformer_sparse_array():
  function test_column_transformer_list (line 416) | def test_column_transformer_list():
  function test_column_transformer_sparse_stacking (line 436) | def test_column_transformer_sparse_stacking():
  function test_column_transformer_mixed_cols_sparse (line 461) | def test_column_transformer_mixed_cols_sparse():
  function test_column_transformer_sparse_threshold (line 483) | def test_column_transformer_sparse_threshold():
  function test_column_transformer_error_msg_1D (line 535) | def test_column_transformer_error_msg_1D():
  function test_2D_transformer_output (line 552) | def test_2D_transformer_output():
  function test_2D_transformer_output_pandas (line 566) | def test_2D_transformer_output_pandas():
  function test_column_transformer_invalid_columns (line 583) | def test_column_transformer_invalid_columns(remainder):
  function test_column_transformer_invalid_transformer (line 618) | def test_column_transformer_invalid_transformer():
  function test_make_column_transformer (line 633) | def test_make_column_transformer():
  function test_make_column_transformer_pandas (line 643) | def test_make_column_transformer_pandas():
  function test_make_column_transformer_kwargs (line 653) | def test_make_column_transformer_kwargs():
  function test_make_column_transformer_remainder_transformer (line 683) | def test_make_column_transformer_remainder_transformer():
  function test_column_transformer_get_set_params (line 693) | def test_column_transformer_get_set_params():
  function test_column_transformer_named_estimators (line 740) | def test_column_transformer_named_estimators():
  function test_column_transformer_cloning (line 760) | def test_column_transformer_cloning():
  function test_column_transformer_get_feature_names (line 777) | def test_column_transformer_get_feature_names(get_names):
  function test_column_transformer_get_feature_names_pipeline (line 808) | def test_column_transformer_get_feature_names_pipeline(X, keys):
  function test_column_transformer_get_feature_names_dataframe (line 854) | def test_column_transformer_get_feature_names_dataframe():
  function test_column_transformer_special_strings (line 904) | def test_column_transformer_special_strings():
  function test_column_transformer_remainder (line 941) | def test_column_transformer_remainder():
  function test_column_transformer_remainder_numpy (line 1001) | def test_column_transformer_remainder_numpy(key):
  function test_column_transformer_remainder_pandas (line 1029) | def test_column_transformer_remainder_pandas(key):
  function test_column_transformer_remainder_transformer (line 1051) | def test_column_transformer_remainder_transformer(key):
  function test_column_transformer_no_remaining_remainder_transformer (line 1068) | def test_column_transformer_no_remaining_remainder_transformer():
  function test_column_transformer_drops_all_remainder_transformer (line 1079) | def test_column_transformer_drops_all_remainder_transformer():
  function test_column_transformer_sparse_remainder_transformer (line 1095) | def test_column_transformer_sparse_remainder_transformer():
  function test_column_transformer_drop_all_sparse_remainder_transformer (line 1116) | def test_column_transformer_drop_all_sparse_remainder_transformer():
  function test_column_transformer_get_set_params_with_remainder (line 1134) | def test_column_transformer_get_set_params_with_remainder():
  function test_column_transformer_no_estimators (line 1178) | def test_column_transformer_no_estimators():
  function test_column_transformer_verbose (line 1261) | def test_column_transformer_verbose(est, pattern, method, capsys):
  function test_column_transformer_no_estimators_set_params (line 1274) | def test_column_transformer_no_estimators_set_params():
  function test_column_transformer_callable_specifier (line 1279) | def test_column_transformer_callable_specifier():
  function test_column_transformer_callable_specifier_dataframe (line 1295) | def test_column_transformer_callable_specifier_dataframe():
  function test_column_transformer_negative_column_indexes (line 1315) | def test_column_transformer_negative_column_indexes():
  function test_column_transformer_mask_indexing (line 1328) | def test_column_transformer_mask_indexing(array_type):
  function test_n_features_in (line 1341) | def test_n_features_in():
  function test_make_column_selector_with_select_dtypes (line 1370) | def test_make_column_selector_with_select_dtypes(cols, pattern, include,...
  function test_column_transformer_with_make_column_selector (line 1389) | def test_column_transformer_with_make_column_selector():
  function test_make_column_selector_error (line 1420) | def test_make_column_selector_error():
  function test_make_column_selector_pickle (line 1428) | def test_make_column_selector_pickle():
  function test_feature_names_empty_columns (line 1460) | def test_feature_names_empty_columns(empty_col, get_names, expected_names):
  function test_feature_names_out_pandas (line 1487) | def test_feature_names_out_pandas(selector):
  function test_feature_names_out_non_pandas (line 1500) | def test_feature_names_out_non_pandas(selector):
  function test_sk_visual_block_remainder (line 1510) | def test_sk_visual_block_remainder(remainder):
  function test_sk_visual_block_remainder_drop (line 1522) | def test_sk_visual_block_remainder_drop():
  function test_sk_visual_block_remainder_fitted_pandas (line 1533) | def test_sk_visual_block_remainder_fitted_pandas(remainder):
  function test_sk_visual_block_remainder_fitted_numpy (line 1556) | def test_sk_visual_block_remainder_fitted_numpy(remainder):
  function test_column_transformers_get_feature_names_deprecated (line 1571) | def test_column_transformers_get_feature_names_deprecated():
  function test_column_transformer_reordered_column_names_remainder (line 1584) | def test_column_transformer_reordered_column_names_remainder(
  function test_feature_name_validation_missing_columns_drop_passthough (line 1620) | def test_feature_name_validation_missing_columns_drop_passthough():
  function test_get_feature_names_empty_selection (line 1657) | def test_get_feature_names_empty_selection(selector):
  function test_feature_names_in_ (line 1666) | def test_feature_names_in_():
  class TransWithNames (line 1686) | class TransWithNames(Trans):
    method __init__ (line 1687) | def __init__(self, feature_names_out=None):
    method get_feature_names_out (line 1690) | def get_feature_names_out(self, input_features=None):
  function test_verbose_feature_names_out_true (line 1763) | def test_verbose_feature_names_out_true(transformers, remainder, expecte...
  function test_verbose_feature_names_out_false (line 1838) | def test_verbose_feature_names_out_false(transformers, remainder, expect...
  function test_verbose_feature_names_out_false_errors (line 1926) | def test_verbose_feature_names_out_false_errors(

FILE: sklearn/compose/tests/test_target.py
  function test_transform_target_regressor_error (line 27) | def test_transform_target_regressor_error():
  function test_transform_target_regressor_invertible (line 60) | def test_transform_target_regressor_invertible():
  function _check_standard_scaled (line 83) | def _check_standard_scaled(y, y_pred):
  function _check_shifted_by_one (line 89) | def _check_shifted_by_one(y, y_pred):
  function test_transform_target_regressor_functions (line 93) | def test_transform_target_regressor_functions():
  function test_transform_target_regressor_functions_multioutput (line 112) | def test_transform_target_regressor_functions_multioutput():
  function test_transform_target_regressor_1d_transformer (line 133) | def test_transform_target_regressor_1d_transformer(X, y):
  function test_transform_target_regressor_2d_transformer (line 164) | def test_transform_target_regressor_2d_transformer(X, y):
  function test_transform_target_regressor_2d_transformer_multioutput (line 198) | def test_transform_target_regressor_2d_transformer_multioutput():
  function test_transform_target_regressor_3d_target (line 224) | def test_transform_target_regressor_3d_target():
  function test_transform_target_regressor_multi_to_single (line 245) | def test_transform_target_regressor_multi_to_single():
  class DummyCheckerArrayTransformer (line 277) | class DummyCheckerArrayTransformer(TransformerMixin, BaseEstimator):
    method fit (line 278) | def fit(self, X, y=None):
    method transform (line 282) | def transform(self, X):
    method inverse_transform (line 286) | def inverse_transform(self, X):
  class DummyCheckerListRegressor (line 291) | class DummyCheckerListRegressor(DummyRegressor):
    method fit (line 292) | def fit(self, X, y, sample_weight=None):
    method predict (line 296) | def predict(self, X):
  function test_transform_target_regressor_ensure_y_array (line 301) | def test_transform_target_regressor_ensure_y_array():
  class DummyTransformer (line 319) | class DummyTransformer(TransformerMixin, BaseEstimator):
    method __init__ (line 322) | def __init__(self, fit_counter=0):
    method fit (line 325) | def fit(self, X, y=None):
    method transform (line 329) | def transform(self, X):
    method inverse_transform (line 332) | def inverse_transform(self, X):
  function test_transform_target_regressor_count_fit (line 337) | def test_transform_target_regressor_count_fit(check_inverse):
  class DummyRegressorWithExtraFitParams (line 348) | class DummyRegressorWithExtraFitParams(DummyRegressor):
    method fit (line 349) | def fit(self, X, y, sample_weight=None, check_input=True):
  function test_transform_target_regressor_pass_fit_parameters (line 356) | def test_transform_target_regressor_pass_fit_parameters():
  function test_transform_target_regressor_route_pipeline (line 366) | def test_transform_target_regressor_route_pipeline():
  class DummyRegressorWithExtraPredictParams (line 380) | class DummyRegressorWithExtraPredictParams(DummyRegressor):
    method predict (line 381) | def predict(self, X, check_input=True):
  function test_transform_target_regressor_pass_extra_predict_parameters (line 389) | def test_transform_target_regressor_pass_extra_predict_parameters():

FILE: sklearn/conftest.py
  function _fetch_fixture (line 41) | def _fetch_fixture(f):
  function pytest_collection_modifyitems (line 68) | def pytest_collection_modifyitems(config, items):
  function pyplot (line 186) | def pyplot():
  function pytest_runtest_setup (line 204) | def pytest_runtest_setup(item):
  function pytest_configure (line 225) | def pytest_configure(config):

FILE: sklearn/covariance/_elliptic_envelope.py
  class EllipticEnvelope (line 12) | class EllipticEnvelope(OutlierMixin, MinCovDet):
    method __init__ (line 141) | def __init__(
    method fit (line 158) | def fit(self, X, y=None):
    method decision_function (line 184) | def decision_function(self, X):
    method score_samples (line 204) | def score_samples(self, X):
    method predict (line 220) | def predict(self, X):
    method score (line 240) | def score(self, X, y, sample_weight=None):

FILE: sklearn/covariance/_empirical_covariance.py
  function log_likelihood (line 24) | def log_likelihood(emp_cov, precision):
  function empirical_covariance (line 51) | def empirical_covariance(X, *, assume_centered=False):
  class EmpiricalCovariance (line 100) | class EmpiricalCovariance(BaseEstimator):
    method __init__ (line 170) | def __init__(self, *, store_precision=True, assume_centered=False):
    method _set_covariance (line 174) | def _set_covariance(self, covariance):
    method get_precision (line 195) | def get_precision(self):
    method fit (line 209) | def fit(self, X, y=None):
    method score (line 236) | def score(self, X_test, y=None):
    method error_norm (line 267) | def error_norm(self, comp_cov, norm="frobenius", scaling=True, squared...
    method mahalanobis (line 318) | def mahalanobis(self, X):

FILE: sklearn/covariance/_graph_lasso.py
  function _objective (line 33) | def _objective(mle, precision_, alpha):
  function _dual_gap (line 46) | def _dual_gap(emp_cov, precision_, alpha):
  function alpha_max (line 58) | def alpha_max(emp_cov):
  class _DictWithDeprecatedKeys (line 77) | class _DictWithDeprecatedKeys(dict):
    method __init__ (line 82) | def __init__(self, **kwargs):
    method __getitem__ (line 86) | def __getitem__(self, key):
    method _set_deprecated (line 95) | def _set_deprecated(self, value, *, new_key, deprecated_key):
  function graphical_lasso (line 101) | def graphical_lasso(
  class GraphicalLasso (line 336) | class GraphicalLasso(EmpiricalCovariance):
    method __init__ (line 432) | def __init__(
    method fit (line 451) | def fit(self, X, y=None):
  function graphical_lasso_path (line 489) | def graphical_lasso_path(
  class GraphicalLassoCV (line 608) | class GraphicalLassoCV(GraphicalLasso):
    method __init__ (line 813) | def __init__(
    method fit (line 840) | def fit(self, X, y=None):
    method grid_scores_ (line 1018) | def grid_scores_(self):
    method cv_alphas_ (line 1038) | def cv_alphas_(self):

FILE: sklearn/covariance/_robust_covariance.py
  function c_step (line 29) | def c_step(
  function _c_step (line 107) | def _c_step(
  function select_candidates (line 208) | def select_candidates(
  function fast_mcd (line 354) | def fast_mcd(
  class MinCovDet (line 576) | class MinCovDet(EmpiricalCovariance):
    method __init__ (line 703) | def __init__(
    method fit (line 716) | def fit(self, X, y=None):
    method correct_covariance (line 769) | def correct_covariance(self, data):
    method reweight_covariance (line 809) | def reweight_covariance(self, data):

FILE: sklearn/covariance/_shrunk_covariance.py
  function shrunk_covariance (line 27) | def shrunk_covariance(emp_cov, shrinkage=0.1):
  class ShrunkCovariance (line 64) | class ShrunkCovariance(EmpiricalCovariance):
    method __init__ (line 148) | def __init__(self, *, store_precision=True, assume_centered=False, shr...
    method fit (line 154) | def fit(self, X, y=None):
  function ledoit_wolf_shrinkage (line 188) | def ledoit_wolf_shrinkage(X, assume_centered=False, block_size=1000):
  function ledoit_wolf (line 283) | def ledoit_wolf(X, *, assume_centered=False, block_size=1000):
  class LedoitWolf (line 347) | class LedoitWolf(EmpiricalCovariance):
    method __init__ (line 448) | def __init__(self, *, store_precision=True, assume_centered=False, blo...
    method fit (line 454) | def fit(self, X, y=None):
  function oas (line 488) | def oas(X, *, assume_centered=False):
  class OAS (line 553) | class OAS(EmpiricalCovariance):
    method fit (line 656) | def fit(self, X, y=None):

FILE: sklearn/covariance/tests/test_covariance.py
  function test_covariance (line 32) | def test_covariance():
  function test_shrunk_covariance (line 79) | def test_shrunk_covariance():
  function test_ledoit_wolf (line 112) | def test_ledoit_wolf():
  function _naive_ledoit_wolf_shrinkage (line 198) | def _naive_ledoit_wolf_shrinkage(X):
  function test_ledoit_wolf_small (line 223) | def test_ledoit_wolf_small():
  function test_ledoit_wolf_large (line 233) | def test_ledoit_wolf_large():
  function test_ledoit_wolf_empty_array (line 251) | def test_ledoit_wolf_empty_array(ledoit_wolf_fitting_function):
  function test_oas (line 258) | def test_oas():
  function test_EmpiricalCovariance_validates_mahalanobis (line 331) | def test_EmpiricalCovariance_validates_mahalanobis():

FILE: sklearn/covariance/tests/test_elliptic_envelope.py
  function test_elliptic_envelope (line 15) | def test_elliptic_envelope():
  function test_score_samples (line 36) | def test_score_samples():

FILE: sklearn/covariance/tests/test_graphical_lasso.py
  function test_graphical_lasso (line 25) | def test_graphical_lasso(random_state=0):
  function test_graphical_lasso_iris (line 68) | def test_graphical_lasso_iris():
  function test_graph_lasso_2D (line 95) | def test_graph_lasso_2D():
  function test_graphical_lasso_iris_singular (line 109) | def test_graphical_lasso_iris_singular():
  function test_graphical_lasso_cv (line 141) | def test_graphical_lasso_cv(random_state=1):
  function test_graphical_lasso_cv_grid_scores_and_cv_alphas_deprecated (line 163) | def test_graphical_lasso_cv_grid_scores_and_cv_alphas_deprecated():
  function test_graphical_lasso_cv_scores (line 202) | def test_graphical_lasso_cv_scores(suffix):
  function test_graphical_lasso_cv_scores_deprecated (line 239) | def test_graphical_lasso_cv_scores_deprecated():

FILE: sklearn/covariance/tests/test_robust_covariance.py
  function test_mcd (line 23) | def test_mcd():
  function test_fast_mcd_on_invalid_input (line 43) | def test_fast_mcd_on_invalid_input():
  function test_mcd_class_on_invalid_input (line 50) | def test_mcd_class_on_invalid_input():
  function launch_mcd_on_dataset (line 58) | def launch_mcd_on_dataset(
  function test_mcd_issue1127 (line 86) | def test_mcd_issue1127():
  function test_mcd_issue3367 (line 95) | def test_mcd_issue3367():
  function test_mcd_support_covariance_is_zero (line 127) | def test_mcd_support_covariance_is_zero():
  function test_mcd_increasing_det_warning (line 143) | def test_mcd_increasing_det_warning():

FILE: sklearn/cross_decomposition/_pls.py
  function _pinv2_old (line 35) | def _pinv2_old(a):
  function _get_first_singular_vectors_power_method (line 53) | def _get_first_singular_vectors_power_method(
  function _get_first_singular_vectors_svd (line 112) | def _get_first_singular_vectors_svd(X, Y):
  function _center_scale_xy (line 122) | def _center_scale_xy(X, Y, scale=True):
  function _svd_flip_1d (line 148) | def _svd_flip_1d(u, v):
  class _PLS (line 158) | class _PLS(
    method __init__ (line 171) | def __init__(
    method fit (line 192) | def fit(self, X, Y):
    method transform (line 366) | def transform(self, X, Y=None, copy=True):
    method inverse_transform (line 405) | def inverse_transform(self, X, Y=None):
    method predict (line 449) | def predict(self, X, copy=True):
    method fit_transform (line 479) | def fit_transform(self, X, y=None):
    method norm_y_weights (line 505) | def norm_y_weights(self):
    method x_mean_ (line 513) | def x_mean_(self):
    method y_mean_ (line 521) | def y_mean_(self):
    method x_std_ (line 529) | def x_std_(self):
    method y_std_ (line 537) | def y_std_(self):
    method x_scores_ (line 541) | def x_scores_(self):
    method y_scores_ (line 555) | def y_scores_(self):
    method _more_tags (line 567) | def _more_tags(self):
  class PLSRegression (line 571) | class PLSRegression(_PLS):
    method __init__ (line 670) | def __init__(
  class PLSCanonical (line 685) | class PLSCanonical(_PLS):
    method __init__ (line 799) | def __init__(
  class CCA (line 821) | class CCA(_PLS):
    method __init__ (line 919) | def __init__(
  class PLSSVD (line 934) | class PLSSVD(TransformerMixin, BaseEstimator):
    method __init__ (line 1018) | def __init__(self, n_components=2, *, scale=True, copy=True):
    method fit (line 1023) | def fit(self, X, Y):
    method x_scores_ (line 1091) | def x_scores_(self):
    method y_scores_ (line 1101) | def y_scores_(self):
    method x_mean_ (line 1109) | def x_mean_(self):
    method y_mean_ (line 1117) | def y_mean_(self):
    method x_std_ (line 1125) | def x_std_(self):
    method y_std_ (line 1133) | def y_std_(self):
    method transform (line 1136) | def transform(self, X, Y=None):
    method fit_transform (line 1168) | def fit_transform(self, X, y=None):

FILE: sklearn/cross_decomposition/tests/test_pls.py
  function assert_matrix_orthogonal (line 21) | def assert_matrix_orthogonal(M):
  function test_pls_canonical_basics (line 26) | def test_pls_canonical_basics():
  function test_sanity_check_pls_regression (line 66) | def test_sanity_check_pls_regression():
  function test_sanity_check_pls_regression_constant_column_Y (line 124) | def test_sanity_check_pls_regression_constant_column_Y():
  function test_sanity_check_pls_canonical (line 174) | def test_sanity_check_pls_canonical():
  function test_sanity_check_pls_canonical_random (line 236) | def test_sanity_check_pls_canonical_random():
  function test_convergence_fail (line 340) | def test_convergence_fail():
  function test_attibutes_shapes (line 352) | def test_attibutes_shapes(Est):
  function test_univariate_equivalence (line 371) | def test_univariate_equivalence(Est):
  function test_copy (line 386) | def test_copy(Est):
  function _generate_test_scale_and_stability_datasets (line 424) | def _generate_test_scale_and_stability_datasets():
  function test_scale_and_stability (line 458) | def test_scale_and_stability(Est, X, Y):
  function test_n_components_bounds (line 473) | def test_n_components_bounds(Est, n_components):
  function test_n_components_bounds_pls_regression (line 487) | def test_n_components_bounds_pls_regression(n_components):
  function test_scores_deprecations (line 501) | def test_scores_deprecations(Est):
  function test_norm_y_weights_deprecation (line 517) | def test_norm_y_weights_deprecation(Est):
  function test_mean_and_std_deprecation (line 529) | def test_mean_and_std_deprecation(Estimator, attribute):
  function test_singular_value_helpers (line 540) | def test_singular_value_helpers(n_samples, n_features, seed):
  function test_one_component_equivalence (line 554) | def test_one_component_equivalence():
  function test_svd_flip_1d (line 566) | def test_svd_flip_1d():
  function test_loadings_converges (line 581) | def test_loadings_converges():
  function test_pls_constant_y (line 597) | def test_pls_constant_y():

FILE: sklearn/datasets/_base.py
  function get_data_home (line 34) | def get_data_home(data_home=None) -> str:
  function clear_data_home (line 62) | def clear_data_home(data_home=None):
  function _convert_data_dataframe (line 75) | def _convert_data_dataframe(
  function load_files (line 93) | def load_files(
  function load_csv_data (line 247) | def load_csv_data(
  function load_gzip_compressed_csv_data (line 314) | def load_gzip_compressed_csv_data(
  function load_descr (line 378) | def load_descr(descr_file_name, *, descr_module=DESCR_MODULE):
  function load_wine (line 403) | def load_wine(*, return_X_y=False, as_frame=False):
  function load_iris (line 520) | def load_iris(*, return_X_y=False, as_frame=False):
  function load_breast_cancer (line 639) | def load_breast_cancer(*, return_X_y=False, as_frame=False):
  function load_digits (line 783) | def load_digits(*, n_class=10, return_X_y=False, as_frame=False):
  function load_diabetes (line 911) | def load_diabetes(*, return_X_y=False, as_frame=False):
  function load_linnerud (line 1010) | def load_linnerud(*, return_X_y=False, as_frame=False):
  function load_boston (line 1152) | def load_boston(*, return_X_y=False):
  function load_sample_images (line 1307) | def load_sample_images():
  function load_sample_image (line 1356) | def load_sample_image(image_name):
  function _pkl_filepath (line 1397) | def _pkl_filepath(*args, **kwargs):
  function _sha256 (line 1414) | def _sha256(path):
  function _fetch_remote (line 1427) | def _fetch_remote(remote, dirname=None):

FILE: sklearn/datasets/_california_housing.py
  function fetch_california_housing (line 53) | def fetch_california_housing(

FILE: sklearn/datasets/_covtype.py
  function fetch_covtype (line 64) | def fetch_covtype(

FILE: sklearn/datasets/_kddcup99.py
  function fetch_kddcup99 (line 49) | def fetch_kddcup99(
  function _fetch_brute_kddcup99 (line 227) | def _fetch_brute_kddcup99(data_home=None, download_if_missing=True, perc...
  function _mkdirp (line 375) | def _mkdirp(d):

FILE: sklearn/datasets/_lfw.py
  function _check_fetch_lfw (line 76) | def _check_fetch_lfw(data_home=None, funneled=True, download_if_missing=...
  function _load_imgs (line 119) | def _load_imgs(file_paths, slice_, color, resize):
  function _fetch_lfw_people (line 182) | def _fetch_lfw_people(
  function fetch_lfw_people (line 225) | def fetch_lfw_people(
  function _fetch_lfw_pairs (line 353) | def _fetch_lfw_pairs(
  function fetch_lfw_pairs (line 405) | def fetch_lfw_pairs(

FILE: sklearn/datasets/_olivetti_faces.py
  function fetch_olivetti_faces (line 39) | def fetch_olivetti_faces(

FILE: sklearn/datasets/_openml.py
  function _get_local_path (line 44) | def _get_local_path(openml_path: str, data_home: str) -> str:
  function _retry_with_clean_cache (line 48) | def _retry_with_clean_cache(openml_path: str, data_home: Optional[str]) ...
  function _open_openml_url (line 75) | def _open_openml_url(openml_path: str, data_home: Optional[str]):
  class OpenMLError (line 134) | class OpenMLError(ValueError):
  function _get_json_content_from_openml_api (line 140) | def _get_json_content_from_openml_api(
  function _split_sparse_columns (line 183) | def _split_sparse_columns(
  function _sparse_data_to_array (line 219) | def _sparse_data_to_array(
  function _convert_arff_data (line 237) | def _convert_arff_data(
  function _feature_to_dtype (line 298) | def _feature_to_dtype(feature: Dict[str, str]):
  function _convert_arff_data_dataframe (line 316) | def _convert_arff_data_dataframe(
  function _get_data_info_by_name (line 375) | def _get_data_info_by_name(
  function _get_data_description_by_id (line 442) | def _get_data_description_by_id(
  function _get_data_features (line 454) | def _get_data_features(data_id: int, data_home: Optional[str]) -> Openml...
  function _get_data_qualities (line 465) | def _get_data_qualities(data_id: int, data_home: Optional[str]) -> Openm...
  function _get_num_samples (line 478) | def _get_num_samples(data_qualities: OpenmlQualitiesType) -> int:
  function _load_arff_response (line 499) | def _load_arff_response(
  function _download_data_to_bunch (line 544) | def _download_data_to_bunch(
  function _verify_target_data_type (line 672) | def _verify_target_data_type(features_dict, target_columns):
  function _valid_data_column_names (line 699) | def _valid_data_column_names(features_list, target_columns):
  function fetch_openml (line 715) | def fetch_openml(

FILE: sklearn/datasets/_rcv1.py
  function fetch_rcv1 (line 79) | def fetch_rcv1(
  function _inverse_permutation (line 282) | def _inverse_permutation(p):
  function _find_permutation (line 291) | def _find_permutation(a, b):

FILE: sklearn/datasets/_samples_generator.py
  function _generate_hypercube (line 23) | def _generate_hypercube(samples, dimensions, rng):
  function make_classification (line 39) | def make_classification(
  function make_multilabel_classification (line 290) | def make_multilabel_classification(
  function make_hastie_10_2 (line 458) | def make_hastie_10_2(n_samples=12000, *, random_state=None):
  function make_regression (line 506) | def make_regression(
  function make_circles (line 640) | def make_circles(
  function make_moons (line 723) | def make_moons(n_samples=100, *, shuffle=True, noise=None, random_state=...
  function make_blobs (line 792) | def make_blobs(
  function make_friedman1 (line 964) | def make_friedman1(n_samples=100, n_features=10, *, noise=0.0, random_st...
  function make_friedman2 (line 1031) | def make_friedman2(n_samples=100, *, noise=0.0, random_state=None):
  function make_friedman3 (line 1096) | def make_friedman3(n_samples=100, *, noise=0.0, random_state=None):
  function make_low_rank_matrix (line 1161) | def make_low_rank_matrix(
  function make_sparse_coded_signal (line 1237) | def make_sparse_coded_signal(
  function make_sparse_uncorrelated (line 1300) | def make_sparse_uncorrelated(n_samples=100, n_features=10, *, random_sta...
  function make_spd_matrix (line 1351) | def make_spd_matrix(n_dim, *, random_state=None):
  function make_sparse_spd_matrix (line 1384) | def make_sparse_spd_matrix(
  function make_swiss_roll (line 1464) | def make_swiss_roll(n_samples=100, *, noise=0.0, random_state=None, hole...
  function make_s_curve (line 1529) | def make_s_curve(n_samples=100, *, noise=0.0, random_state=None):
  function make_gaussian_quantiles (line 1571) | def make_gaussian_quantiles(
  function _shuffle (line 1667) | def _shuffle(data, random_state=None):
  function make_biclusters (line 1676) | def make_biclusters(
  function make_checkerboard (line 1773) | def make_checkerboard(

FILE: sklearn/datasets/_species_distributions.py
  function _load_coverage (line 77) | def _load_coverage(F, header_length=6, dtype=np.int16):
  function _load_csv (line 93) | def _load_csv(F):
  function construct_grids (line 113) | def construct_grids(batch):
  function fetch_species_distributions (line 140) | def fetch_species_distributions(*, data_home=None, download_if_missing=T...

FILE: sklearn/datasets/_svmlight_format_io.py
  function _load_svmlight_file (line 33) | def _load_svmlight_file(*args, **kwargs):
  function load_svmlight_file (line 42) | def load_svmlight_file(
  function _gen_open (line 177) | def _gen_open(f):
  function _open_and_load (line 196) | def _open_and_load(f, dtype, multilabel, zero_based, query_id, offset=0,...
  function load_svmlight_files (line 219) | def load_svmlight_files(
  function _dump_svmlight (line 366) | def _dump_svmlight(X, y, f, multilabel, one_based, comment, query_id):
  function dump_svmlight_file (line 427) | def dump_svmlight_file(

FILE: sklearn/datasets/_twenty_newsgroups.py
  function _download_20newsgroups (line 65) | def _download_20newsgroups(target_dir, cache_path):
  function strip_newsgroup_header (line 93) | def strip_newsgroup_header(text):
  function strip_newsgroup_quoting (line 112) | def strip_newsgroup_quoting(text):
  function strip_newsgroup_footer (line 127) | def strip_newsgroup_footer(text):
  function fetch_20newsgroups (line 152) | def fetch_20newsgroups(
  function fetch_20newsgroups_vectorized (line 334) | def fetch_20newsgroups_vectorized(

FILE: sklearn/datasets/setup.py
  function configuration (line 6) | def configuration(parent_package="", top_path=None):

FILE: sklearn/datasets/tests/conftest.py
  function hide_available_pandas (line 8) | def hide_available_pandas(monkeypatch):

FILE: sklearn/datasets/tests/test_20news.py
  function test_20news (line 19) | def test_20news(fetch_20newsgroups_fxt):
  function test_20news_length_consistency (line 51) | def test_20news_length_consistency(fetch_20newsgroups_fxt):
  function test_20news_vectorized (line 63) | def test_20news_vectorized(fetch_20newsgroups_vectorized_fxt):
  function test_20news_normalization (line 93) | def test_20news_normalization(fetch_20newsgroups_vectorized_fxt):
  function test_20news_as_frame (line 103) | def test_20news_as_frame(fetch_20newsgroups_vectorized_fxt):
  function test_as_frame_no_pandas (line 128) | def test_as_frame_no_pandas(fetch_20newsgroups_vectorized_fxt, hide_avai...
  function test_outdated_pickle (line 132) | def test_outdated_pickle(fetch_20newsgroups_vectorized_fxt):

FILE: sklearn/datasets/tests/test_base.py
  function _remove_dir (line 38) | def _remove_dir(path):
  function data_home (line 44) | def data_home(tmpdir_factory):
  function load_files_root (line 51) | def load_files_root(tmpdir_factory):
  function test_category_dir_1 (line 58) | def test_category_dir_1(load_files_root):
  function test_category_dir_2 (line 68) | def test_category_dir_2(load_files_root):
  function test_data_home (line 74) | def test_data_home(data_home):
  function test_default_empty_load_files (line 89) | def test_default_empty_load_files(load_files_root):
  function test_default_load_files (line 96) | def test_default_load_files(test_category_dir_1, test_category_dir_2, lo...
  function test_load_files_w_categories_desc_and_encoding (line 106) | def test_load_files_w_categories_desc_and_encoding(
  function test_load_files_wo_load_content (line 121) | def test_load_files_wo_load_content(
  function test_load_csv_data (line 139) | def test_load_csv_data(
  function test_load_csv_data_with_descr (line 149) | def test_load_csv_data_with_descr():
  function test_load_gzip_compressed_csv_data (line 175) | def test_load_gzip_compressed_csv_data(filename, kwargs, expected_shape):
  function test_load_gzip_compressed_csv_data_with_descr (line 180) | def test_load_gzip_compressed_csv_data_with_descr():
  function test_load_sample_images (line 194) | def test_load_sample_images():
  function test_load_sample_image (line 210) | def test_load_sample_image():
  function test_load_missing_sample_image_error (line 219) | def test_load_missing_sample_image_error():
  function test_loader (line 248) | def test_loader(loader_func, data_shape, target_shape, n_target, has_des...
  function test_toy_dataset_frame_dtype (line 281) | def test_toy_dataset_frame_dtype(loader_func, data_dtype, target_dtype):
  function test_loads_dumps_bunch (line 291) | def test_loads_dumps_bunch():
  function test_bunch_pickle_generated_with_0_16_and_read_with_0_17 (line 298) | def test_bunch_pickle_generated_with_0_16_and_read_with_0_17():
  function test_bunch_dir (line 319) | def test_bunch_dir():
  function test_load_boston_warning (line 326) | def test_load_boston_warning():
  function test_load_boston_alternative (line 334) | def test_load_boston_alternative():

FILE: sklearn/datasets/tests/test_california_housing.py
  function test_fetch (line 10) | def test_fetch(fetch_california_housing_fxt):
  function test_fetch_asframe (line 21) | def test_fetch_asframe(fetch_california_housing_fxt):
  function test_pandas_dependency_message (line 31) | def test_pandas_dependency_message(fetch_california_housing_fxt, hide_av...

FILE: sklearn/datasets/tests/test_common.py
  function is_pillow_installed (line 11) | def is_pillow_installed():
  function check_pandas_dependency_message (line 40) | def check_pandas_dependency_message(fetch_func):
  function check_return_X_y (line 54) | def check_return_X_y(bunch, dataset_func):
  function check_as_frame (line 61) | def check_as_frame(
  function _skip_network_tests (line 89) | def _skip_network_tests():
  function _generate_func_supporting_param (line 93) | def _generate_func_supporting_param(param, dataset_type=("load", "fetch")):
  function test_common_check_return_X_y (line 119) | def test_common_check_return_X_y(name, dataset_func):
  function test_common_check_as_frame (line 127) | def test_common_check_as_frame(name, dataset_func):
  function test_common_check_pandas_dependency (line 135) | def test_common_check_pandas_dependency(name, dataset_func):

FILE: sklearn/datasets/tests/test_covtype.py
  function test_fetch (line 9) | def test_fetch(fetch_covtype_fxt):
  function test_fetch_asframe (line 32) | def test_fetch_asframe(fetch_covtype_fxt):
  function test_pandas_dependency_message (line 49) | def test_pandas_dependency_message(fetch_covtype_fxt, hide_available_pan...

FILE: sklearn/datasets/tests/test_kddcup99.py
  function test_fetch_kddcup99_percent10 (line 28) | def test_fetch_kddcup99_percent10(
  function test_fetch_kddcup99_return_X_y (line 39) | def test_fetch_kddcup99_return_X_y(fetch_kddcup99_fxt):
  function test_fetch_kddcup99_as_frame (line 45) | def test_fetch_kddcup99_as_frame(fetch_kddcup99_fxt):
  function test_fetch_kddcup99_shuffle (line 50) | def test_fetch_kddcup99_shuffle(fetch_kddcup99_fxt):
  function test_pandas_dependency_message (line 67) | def test_pandas_dependency_message(fetch_kddcup99_fxt, hide_available_pa...
  function test_corrupted_file_error_message (line 71) | def test_corrupted_file_error_message(fetch_kddcup99_fxt, tmp_path):

FILE: sklearn/datasets/tests/test_lfw.py
  function setup_module (line 42) | def setup_module():
  function teardown_module (line 108) | def teardown_module():
  function test_load_empty_lfw_people (line 116) | def test_load_empty_lfw_people():
  function test_load_fake_lfw_people (line 121) | def test_load_fake_lfw_people():
  function test_load_fake_lfw_people_too_restrictive (line 179) | def test_load_fake_lfw_people_too_restrictive():
  function test_load_empty_lfw_pairs (line 188) | def test_load_empty_lfw_pairs():
  function test_load_fake_lfw_pairs (line 193) | def test_load_fake_lfw_pairs():

FILE: sklearn/datasets/tests/test_olivetti_faces.py
  function test_olivetti_faces (line 13) | def test_olivetti_faces(fetch_olivetti_faces_fxt):

FILE: sklearn/datasets/tests/test_openml.py
  function _test_features_list (line 42) | def _test_features_list(data_id):
  function _fetch_dataset_from_openml (line 91) | def _fetch_dataset_from_openml(
  class _MockHTTPResponse (line 186) | class _MockHTTPResponse:
    method __init__ (line 187) | def __init__(self, data, is_gzip):
    method read (line 191) | def read(self, amt=-1):
    method close (line 194) | def close(self):
    method info (line 197) | def info(self):
    method __iter__ (line 202) | def __iter__(self):
    method __enter__ (line 205) | def __enter__(self):
    method __exit__ (line 208) | def __exit__(self, exc_type, exc_val, exc_tb):
  function _monkey_patch_webbased_functions (line 212) | def _monkey_patch_webbased_functions(context, data_id, gzip_response):
  function test_feature_to_dtype (line 342) | def test_feature_to_dtype(feature, expected_dtype):
  function test_feature_to_dtype_error (line 349) | def test_feature_to_dtype_error(feature):
  function test_fetch_openml_iris_pandas (line 358) | def test_fetch_openml_iris_pandas(monkeypatch):
  function test_fetch_openml_iris_pandas_equal_to_no_frame (line 403) | def test_fetch_openml_iris_pandas_equal_to_no_frame(monkeypatch):
  function test_fetch_openml_iris_multitarget_pandas (line 425) | def test_fetch_openml_iris_multitarget_pandas(monkeypatch):
  function test_fetch_openml_anneal_pandas (line 470) | def test_fetch_openml_anneal_pandas(monkeypatch):
  function test_fetch_openml_cpu_pandas (line 512) | def test_fetch_openml_cpu_pandas(monkeypatch):
  function test_fetch_openml_australian_pandas_error_sparse (line 581) | def test_fetch_openml_australian_pandas_error_sparse(monkeypatch):
  function test_fetch_openml_as_frame_auto (line 594) | def test_fetch_openml_as_frame_auto(monkeypatch):
  function test_convert_arff_data_dataframe_warning_low_memory_pandas (line 611) | def test_convert_arff_data_dataframe_warning_low_memory_pandas(monkeypat...
  function test_fetch_openml_adultcensus_pandas_return_X_y (line 626) | def test_fetch_openml_adultcensus_pandas_return_X_y(monkeypatch):
  function test_fetch_openml_adultcensus_pandas (line 657) | def test_fetch_openml_adultcensus_pandas(monkeypatch):
  function test_fetch_openml_miceprotein_pandas (line 697) | def test_fetch_openml_miceprotein_pandas(monkeypatch):
  function test_fetch_openml_emotions_pandas (line 741) | def test_fetch_openml_emotions_pandas(monkeypatch):
  function test_fetch_openml_titanic_pandas (line 790) | def test_fetch_openml_titanic_pandas(monkeypatch):
  function test_fetch_openml_iris (line 872) | def test_fetch_openml_iris(monkeypatch, gzip_response):
  function test_decode_iris (line 888) | def test_decode_iris(monkeypatch):
  function test_fetch_openml_iris_multitarget (line 895) | def test_fetch_openml_iris_multitarget(monkeypatch, gzip_response):
  function test_fetch_openml_anneal (line 922) | def test_fetch_openml_anneal(monkeypatch, gzip_response):
  function test_decode_anneal (line 948) | def test_decode_anneal(monkeypatch):
  function test_fetch_openml_anneal_multitarget (line 955) | def test_fetch_openml_anneal_multitarget(monkeypatch, gzip_response):
  function test_fetch_openml_cpu (line 982) | def test_fetch_openml_cpu(monkeypatch, gzip_response):
  function test_decode_cpu (line 1007) | def test_decode_cpu(monkeypatch):
  function test_fetch_openml_australian (line 1014) | def test_fetch_openml_australian(monkeypatch, gzip_response):
  function test_fetch_openml_adultcensus (line 1048) | def test_fetch_openml_adultcensus(monkeypatch, gzip_response):
  function test_fetch_openml_miceprotein (line 1075) | def test_fetch_openml_miceprotein(monkeypatch, gzip_response):
  function test_fetch_openml_emotions (line 1105) | def test_fetch_openml_emotions(monkeypatch, gzip_response):
  function test_decode_emotions (line 1138) | def test_decode_emotions(monkeypatch):
  function test_open_openml_url_cache (line 1145) | def test_open_openml_url_cache(monkeypatch, gzip_response, tmpdir):
  function test_open_openml_url_unlinks_local_path (line 1163) | def test_open_openml_url_unlinks_local_path(
  function test_retry_with_clean_cache (line 1185) | def test_retry_with_clean_cache(tmpdir):
  function test_retry_with_clean_cache_http_error (line 1208) | def test_retry_with_clean_cache_http_error(tmpdir):
  function test_fetch_openml_cache (line 1225) | def test_fetch_openml_cache(monkeypatch, gzip_response, tmpdir):
  function test_fetch_openml_notarget (line 1259) | def test_fetch_openml_notarget(monkeypatch, gzip_response):
  function test_fetch_openml_inactive (line 1274) | def test_fetch_openml_inactive(monkeypatch, gzip_response):
  function test_fetch_nonexiting (line 1291) | def test_fetch_nonexiting(monkeypatch, gzip_response):
  function test_raises_illegal_multitarget (line 1302) | def test_raises_illegal_multitarget(monkeypatch, gzip_response):
  function test_warn_ignore_attribute (line 1313) | def test_warn_ignore_attribute(monkeypatch, gzip_response):
  function test_string_attribute_without_dataframe (line 1353) | def test_string_attribute_without_dataframe(monkeypatch, gzip_response):
  function test_dataset_with_openml_error (line 1366) | def test_dataset_with_openml_error(monkeypatch, gzip_response):
  function test_dataset_with_openml_warning (line 1375) | def test_dataset_with_openml_warning(monkeypatch, gzip_response):
  function test_illegal_column (line 1384) | def test_illegal_column(monkeypatch, gzip_response):
  function test_fetch_openml_raises_missing_values_target (line 1396) | def test_fetch_openml_raises_missing_values_target(monkeypatch, gzip_res...
  function test_fetch_openml_raises_illegal_argument (line 1404) | def test_fetch_openml_raises_illegal_argument():
  function test_fetch_openml_with_ignored_feature (line 1422) | def test_fetch_openml_with_ignored_feature(monkeypatch, gzip_response):
  function test_fetch_openml_verify_checksum (line 1442) | def test_fetch_openml_verify_checksum(monkeypatch, as_frame, cache, tmpd...
  function test_convert_arff_data_type (line 1484) | def test_convert_arff_data_type():
  function test_missing_values_pandas (line 1503) | def test_missing_values_pandas(monkeypatch):

FILE: sklearn/datasets/tests/test_rcv1.py
  function test_fetch_rcv1 (line 13) | def test_fetch_rcv1(fetch_rcv1_fxt):

FILE: sklearn/datasets/tests/test_samples_generator.py
  function test_make_classification (line 35) | def test_make_classification():
  function test_make_classification_informative_features (line 83) | def test_make_classification_informative_features():
  function test_make_classification_weights_type (line 208) | def test_make_classification_weights_type(weights, err_type, err_msg):
  function test_make_classification_weights_array_or_list_ok (line 214) | def test_make_classification_weights_array_or_list_ok(kwargs):
  function test_make_multilabel_classification_return_sequences (line 221) | def test_make_multilabel_classification_return_sequences():
  function test_make_multilabel_classification_return_indicator (line 238) | def test_make_multilabel_classification_return_indicator():
  function test_make_multilabel_classification_return_indicator_sparse (line 269) | def test_make_multilabel_classification_return_indicator_sparse():
  function test_make_multilabel_classification_valid_arguments (line 291) | def test_make_multilabel_classification_valid_arguments(params, err_msg):
  function test_make_hastie_10_2 (line 296) | def test_make_hastie_10_2():
  function test_make_regression (line 303) | def test_make_regression():
  function test_make_regression_multitarget (line 328) | def test_make_regression_multitarget():
  function test_make_blobs (line 348) | def test_make_blobs():
  function test_make_blobs_n_samples_list (line 366) | def test_make_blobs_n_samples_list():
  function test_make_blobs_n_samples_list_with_centers (line 376) | def test_make_blobs_n_samples_list_with_centers():
  function test_make_blobs_n_samples_centers_none (line 395) | def test_make_blobs_n_samples_centers_none(n_samples):
  function test_make_blobs_return_centers (line 405) | def test_make_blobs_return_centers():
  function test_make_blobs_error (line 415) | def test_make_blobs_error():
  function test_make_friedman1 (line 438) | def test_make_friedman1():
  function test_make_friedman2 (line 453) | def test_make_friedman2():
  function test_make_friedman3 (line 464) | def test_make_friedman3():
  function test_make_low_rank_matrix (line 475) | def test_make_low_rank_matrix():
  function test_make_sparse_coded_signal (line 492) | def test_make_sparse_coded_signal():
  function test_make_sparse_uncorrelated (line 505) | def test_make_sparse_uncorrelated():
  function test_make_spd_matrix (line 512) | def test_make_spd_matrix():
  function test_make_swiss_roll (line 527) | def test_make_swiss_roll(hole):
  function test_make_s_curve (line 536) | def test_make_s_curve():
  function test_make_biclusters (line 545) | def test_make_biclusters():
  function test_make_checkerboard (line 565) | def test_make_checkerboard():
  function test_make_moons (line 592) | def test_make_moons():
  function test_make_moons_unbalanced (line 602) | def test_make_moons_unbalanced():
  function test_make_circles (line 623) | def test_make_circles():
  function test_make_circles_unbalanced (line 656) | def test_make_circles_unbalanced():

FILE: sklearn/datasets/tests/test_svmlight_format.py
  function _load_svmlight_local_test_file (line 30) | def _load_svmlight_local_test_file(filename, **kwargs):
  function test_load_svmlight_file (line 38) | def test_load_svmlight_file():
  function test_load_svmlight_file_fd (line 74) | def test_load_svmlight_file_fd():
  function test_load_svmlight_file_multilabel (line 92) | def test_load_svmlight_file_multilabel():
  function test_load_svmlight_files (line 97) | def test_load_svmlight_files():
  function test_load_svmlight_file_n_features (line 116) | def test_load_svmlight_file_n_features():
  function test_load_compressed (line 134) | def test_load_compressed():
  function test_load_invalid_file (line 162) | def test_load_invalid_file():
  function test_load_invalid_order_file (line 167) | def test_load_invalid_order_file():
  function test_load_zero_based (line 172) | def test_load_zero_based():
  function test_load_zero_based_auto (line 178) | def test_load_zero_based_auto():
  function test_load_with_qid (line 193) | def test_load_with_qid():
  function test_load_large_qid (line 213) | def test_load_large_qid():
  function test_load_invalid_file2 (line 228) | def test_load_invalid_file2():
  function test_not_a_filename (line 236) | def test_not_a_filename():
  function test_invalid_filename (line 243) | def test_invalid_filename():
  function test_dump (line 248) | def test_dump():
  function test_dump_multilabel (line 317) | def test_dump_multilabel():
  function test_dump_concise (line 331) | def test_dump_concise():
  function test_dump_comment (line 362) | def test_dump_comment():
  function test_dump_invalid (line 395) | def test_dump_invalid():
  function test_dump_query_id (line 408) | def test_dump_query_id():
  function test_load_with_long_qid (line 423) | def test_load_with_long_qid():
  function test_load_zeros (line 459) | def test_load_zeros():
  function test_load_with_offsets (line 475) | def test_load_with_offsets(sparsity, n_samples, n_features):
  function test_load_offset_exhaustive_splits (line 511) | def test_load_offset_exhaustive_splits():
  function test_load_with_offsets_error (line 553) | def test_load_with_offsets_error():

FILE: sklearn/decomposition/_base.py
  class _BasePCA (line 19) | class _BasePCA(
    method get_covariance (line 28) | def get_covariance(self):
    method get_precision (line 49) | def get_precision(self):
    method fit (line 82) | def fit(self, X, y=None):
    method transform (line 99) | def transform(self, X):
    method inverse_transform (line 127) | def inverse_transform(self, X):
    method _n_features_out (line 161) | def _n_features_out(self):

FILE: sklearn/decomposition/_dict_learning.py
  function _check_positive_coding (line 26) | def _check_positive_coding(method, positive):
  function _sparse_encode (line 33) | def _sparse_encode(
  function sparse_encode (line 226) | def sparse_encode(
  function _update_dict (line 410) | def _update_dict(
  function dict_learning (line 490) | def dict_learning(
  function dict_learning_online (line 720) | def dict_learning_online(
  class _BaseSparseCoding (line 1017) | class _BaseSparseCoding(_ClassNamePrefixFeaturesOutMixin, TransformerMix...
    method __init__ (line 1020) | def __init__(
    method _transform (line 1038) | def _transform(self, X, dictionary):
    method transform (line 1080) | def transform(self, X):
  class SparseCoder (line 1101) | class SparseCoder(_BaseSparseCoding, BaseEstimator):
    method __init__ (line 1230) | def __init__(
    method fit (line 1253) | def fit(self, X, y=None):
    method components_ (line 1280) | def components_(self):
    method transform (line 1283) | def transform(self, X, y=None):
    method _more_tags (line 1305) | def _more_tags(self):
    method n_components_ (line 1309) | def n_components_(self):
    method n_features_in_ (line 1314) | def n_features_in_(self):
    method _n_features_out (line 1319) | def _n_features_out(self):
  class DictionaryLearning (line 1324) | class DictionaryLearning(_BaseSparseCoding, BaseEstimator):
    method __init__ (line 1508) | def __init__(
    method fit (line 1550) | def fit(self, X, y=None):
    method _n_features_out (line 1596) | def _n_features_out(self):
  class MiniBatchDictionaryLearning (line 1601) | class MiniBatchDictionaryLearning(_BaseSparseCoding, BaseEstimator):
    method __init__ (line 1789) | def __init__(
    method fit (line 1832) | def fit(self, X, y=None):
    method partial_fit (line 1879) | def partial_fit(self, X, y=None, iter_offset=None):
    method _n_features_out (line 1941) | def _n_features_out(self):

FILE: sklearn/decomposition/_factor_analysis.py
  class FactorAnalysis (line 35) | class FactorAnalysis(_ClassNamePrefixFeaturesOutMixin, TransformerMixin,...
    method __init__ (line 162) | def __init__(
    method fit (line 191) | def fit(self, X, y=None):
    method transform (line 303) | def transform(self, X):
    method get_covariance (line 333) | def get_covariance(self):
    method get_precision (line 349) | def get_precision(self):
    method score_samples (line 377) | def score_samples(self, X):
    method score (line 399) | def score(self, X, y=None):
    method _rotate (line 417) | def _rotate(self, components, n_components=None, tol=1e-6):
    method _n_features_out (line 430) | def _n_features_out(self):
  function _ortho_rotation (line 435) | def _ortho_rotation(components, method="varimax", tol=1e-6, max_iter=100):

FILE: sklearn/decomposition/_fastica.py
  function _gs_decorrelation (line 27) | def _gs_decorrelation(w, W, j):
  function _sym_decorrelation (line 52) | def _sym_decorrelation(W):
  function _ica_def (line 62) | def _ica_def(X, tol, g, fun_args, max_iter, w_init):
  function _ica_par (line 97) | def _ica_par(X, tol, g, fun_args, max_iter, w_init):
  function _logcosh (line 127) | def _logcosh(x, fun_args=None):
  function _exp (line 139) | def _exp(x, fun_args):
  function _cube (line 146) | def _cube(x, fun_args):
  function fastica (line 150) | def fastica(
  class FastICA (line 318) | class FastICA(_ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEs...
    method __init__ (line 439) | def __init__(
    method _fit (line 463) | def _fit(self, X, compute_sources=False):
    method fit_transform (line 632) | def fit_transform(self, X, y=None):
    method fit (line 652) | def fit(self, X, y=None):
    method transform (line 672) | def transform(self, X, copy=True):
    method inverse_transform (line 700) | def inverse_transform(self, X, copy=True):
    method _n_features_out (line 726) | def _n_features_out(self):

FILE: sklearn/decomposition/_incremental_pca.py
  class IncrementalPCA (line 15) | class IncrementalPCA(_BasePCA):
    method __init__ (line 181) | def __init__(self, n_components=None, *, whiten=False, copy=True, batc...
    method fit (line 187) | def fit(self, X, y=None):
    method partial_fit (line 236) | def partial_fit(self, X, y=None, check_input=True):
    method transform (line 353) | def transform(self, X):

FILE: sklearn/decomposition/_kernel_pca.py
  class KernelPCA (line 24) | class KernelPCA(_ClassNamePrefixFeaturesOutMixin, TransformerMixin, Base...
    method __init__ (line 240) | def __init__(
    method _pairwise (line 284) | def _pairwise(self):
    method lambdas_ (line 294) | def lambdas_(self):
    method alphas_ (line 303) | def alphas_(self):
    method _get_kernel (line 306) | def _get_kernel(self, X, Y=None):
    method _fit_transform (line 315) | def _fit_transform(self, K):
    method _fit_inverse_transform (line 401) | def _fit_inverse_transform(self, X_transformed, X):
    method fit (line 413) | def fit(self, X, y=None):
    method fit_transform (line 446) | def fit_transform(self, X, y=None, **params):
    method transform (line 477) | def transform(self, X):
    method inverse_transform (line 507) | def inverse_transform(self, X):
    method _more_tags (line 558) | def _more_tags(self):
    method _n_features_out (line 565) | def _n_features_out(self):

FILE: sklearn/decomposition/_lda.py
  function _update_doc_distribution (line 34) | def _update_doc_distribution(
  class LatentDirichletAllocation (line 141) | class LatentDirichletAllocation(
    method __init__ (line 323) | def __init__(
    method _check_params (line 360) | def _check_params(self):
    method _init_latent_vars (line 380) | def _init_latent_vars(self, n_features):
    method _e_step (line 409) | def _e_step(self, X, cal_sstats, random_init, parallel=None):
    method _em_step (line 475) | def _em_step(self, X, total_samples, batch_update, parallel=None):
    method _more_tags (line 529) | def _more_tags(self):
    method _check_non_neg_array (line 532) | def _check_non_neg_array(self, X, reset_n_features, whom):
    method partial_fit (line 546) | def partial_fit(self, X, y=None):
    method fit (line 593) | def fit(self, X, y=None):
    method _unnormalized_transform (line 676) | def _unnormalized_transform(self, X):
    method transform (line 693) | def transform(self, X):
    method _approx_bound (line 717) | def _approx_bound(self, X, doc_topic_distr, sub_sampling):
    method score (line 796) | def score(self, X, y=None):
    method _perplexity_precomp_distr (line 821) | def _perplexity_precomp_distr(self, X, doc_topic_distr=None, sub_sampl...
    method perplexity (line 865) | def perplexity(self, X, sub_sampling=False):
    method _n_features_out (line 894) | def _n_features_out(self):

FILE: sklearn/decomposition/_nmf.py
  function norm (line 30) | def norm(x):
  function trace_dot (line 43) | def trace_dot(X, Y):
  function _check_init (line 56) | def _check_init(A, shape, whom):
  function _beta_divergence (line 68) | def _beta_divergence(X, W, H, beta, square_root=False):
  function _special_sparse_dot (line 174) | def _special_sparse_dot(W, H, X):
  function _compute_regularization (line 195) | def _compute_regularization(alpha, alpha_W, alpha_H, l1_ratio, regulariz...
  function _beta_loss_to_float (line 218) | def _beta_loss_to_float(beta_loss):
  function _initialize_nmf (line 232) | def _initialize_nmf(X, n_components, init=None, eps=1e-6, random_state=N...
  function _update_coordinate_descent (line 383) | def _update_coordinate_descent(X, W, Ht, l1_reg, l2_reg, shuffle, random...
  function _fit_coordinate_descent (line 413) | def _fit_coordinate_descent(
  function _multiplicative_update_w (line 533) | def _multiplicative_update_w(
  function _multiplicative_update_h (line 639) | def _multiplicative_update_h(X, W, H, beta_loss, l1_reg_H, l2_reg_H, gam...
  function _fit_multiplicative_update (line 721) | def _fit_multiplicative_update(
  function non_negative_factorization (line 870) | def non_negative_factorization(
  class NMF (line 1112) | class NMF(_ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstima...
    method __init__ (line 1334) | def __init__(
    method _more_tags (line 1367) | def _more_tags(self):
    method _check_params (line 1370) | def _check_params(self, X):
    method _check_w_h (line 1462) | def _check_w_h(self, X, W, H, update_H):
    method _scale_regularization (line 1493) | def _scale_regularization(self, X):
    method fit_transform (line 1512) | def fit_transform(self, X, y=None, W=None, H=None):
    method _fit_transform (line 1554) | def _fit_transform(self, X, y=None, W=None, H=None, update_H=True):
    method fit (line 1650) | def fit(self, X, y=None, **params):
    method transform (line 1674) | def transform(self, X):
    method inverse_transform (line 1698) | def inverse_transform(self, W):
    method _n_features_out (line 1717) | def _n_features_out(self):

FILE: sklearn/decomposition/_pca.py
  function _assess_dimension (line 30) | def _assess_dimension(spectrum, rank, n_samples):
  function _infer_dimension (line 104) | def _infer_dimension(spectrum, n_samples):
  class PCA (line 116) | class PCA(_BasePCA):
    method __init__ (line 354) | def __init__(
    method fit (line 375) | def fit(self, X, y=None):
    method fit_transform (line 402) | def fit_transform(self, X, y=None):
    method _fit (line 436) | def _fit(self, X):
    method _fit_full (line 482) | def _fit_full(self, X, n_components):
    method _fit_truncated (line 548) | def _fit_truncated(self, X, n_components, svd_solver):
    method score_samples (line 624) | def score_samples(self, X):
    method score (line 651) | def score(self, X, y=None):
    method _more_tags (line 673) | def _more_tags(self):

FILE: sklearn/decomposition/_sparse_pca.py
  class SparsePCA (line 14) | class SparsePCA(_ClassNamePrefixFeaturesOutMixin, TransformerMixin, Base...
    method __init__ (line 128) | def __init__(
    method fit (line 155) | def fit(self, X, y=None):
    method transform (line 207) | def transform(self, X):
    method _n_features_out (line 240) | def _n_features_out(self):
  class MiniBatchSparsePCA (line 245) | class MiniBatchSparsePCA(SparsePCA):
    method __init__ (line 357) | def __init__(
    method fit (line 386) | def fit(self, X, y=None):

FILE: sklearn/decomposition/_truncated_svd.py
  class TruncatedSVD (line 24) | class TruncatedSVD(_ClassNamePrefixFeaturesOutMixin, TransformerMixin, B...
    method __init__ (line 142) | def __init__(
    method fit (line 157) | def fit(self, X, y=None):
    method fit_transform (line 176) | def fit_transform(self, X, y=None):
    method transform (line 239) | def transform(self, X):
    method inverse_transform (line 256) | def inverse_transform(self, X):
    method _more_tags (line 274) | def _more_tags(self):
    method _n_features_out (line 278) | def _n_features_out(self):

FILE: sklearn/decomposition/setup.py
  function configuration (line 6) | def configuration(parent_package="", top_path=None):

FILE: sklearn/decomposition/tests/test_dict_learning.py
  function test_sparse_encode_shapes_omp (line 37) | def test_sparse_encode_shapes_omp():
  function test_dict_learning_shapes (line 48) | def test_dict_learning_shapes():
  function test_dict_learning_overcomplete (line 59) | def test_dict_learning_overcomplete():
  function test_max_iter (line 65) | def test_max_iter():
  function test_dict_learning_lars_positive_parameter (line 122) | def test_dict_learning_lars_positive_parameter():
  function test_dict_learning_positivity (line 140) | def test_dict_learning_positivity(transform_algorithm, positive_code, po...
  function test_dict_learning_lars_dict_positivity (line 163) | def test_dict_learning_lars_dict_positivity(positive_dict):
  function test_dict_learning_lars_code_positivity (line 179) | def test_dict_learning_lars_code_positivity():
  function test_dict_learning_reconstruction (line 195) | def test_dict_learning_reconstruction():
  function test_dict_learning_reconstruction_parallel (line 211) | def test_dict_learning_reconstruction_parallel():
  function test_dict_learning_lassocd_readonly_data (line 229) | def test_dict_learning_lassocd_readonly_data():
  function test_dict_learning_nonzero_coefs (line 246) | def test_dict_learning_nonzero_coefs():
  function test_dict_learning_unknown_fit_algorithm (line 262) | def test_dict_learning_unknown_fit_algorithm():
  function test_dict_learning_split (line 269) | def test_dict_learning_split():
  function test_dict_learning_online_shapes (line 283) | def test_dict_learning_online_shapes():
  function test_dict_learning_online_lars_positive_parameter (line 294) | def test_dict_learning_online_lars_positive_parameter():
  function test_minibatch_dictionary_learning_positivity (line 311) | def test_minibatch_dictionary_learning_positivity(
  function test_minibatch_dictionary_learning_lars (line 336) | def test_minibatch_dictionary_learning_lars(positive_dict):
  function test_dict_learning_online_positivity (line 355) | def test_dict_learning_online_positivity(positive_code, positive_dict):
  function test_dict_learning_online_verbosity (line 378) | def test_dict_learning_online_verbosity():
  function test_dict_learning_online_estimator_shapes (line 407) | def test_dict_learning_online_estimator_shapes():
  function test_dict_learning_online_overcomplete (line 414) | def test_dict_learning_online_overcomplete():
  function test_dict_learning_online_initialization (line 420) | def test_dict_learning_online_initialization():
  function test_dict_learning_online_readonly_initialization (line 430) | def test_dict_learning_online_readonly_initialization():
  function test_dict_learning_online_partial_fit (line 440) | def test_dict_learning_online_partial_fit():
  function test_dict_learning_iter_offset (line 465) | def test_dict_learning_iter_offset():
  function test_sparse_encode_shapes (line 482) | def test_sparse_encode_shapes():
  function test_sparse_encode_positivity (line 494) | def test_sparse_encode_positivity(algo, positive):
  function test_sparse_encode_unavailable_positivity (line 507) | def test_sparse_encode_unavailable_positivity(algo):
  function test_sparse_encode_input (line 518) | def test_sparse_encode_input():
  function test_sparse_encode_error (line 530) | def test_sparse_encode_error():
  function test_sparse_encode_error_default_sparsity (line 540) | def test_sparse_encode_error_default_sparsity():
  function test_unknown_method (line 548) | def test_unknown_method():
  function test_sparse_coder_estimator (line 556) | def test_sparse_coder_estimator():
  function test_sparse_coder_estimator_clone (line 568) | def test_sparse_coder_estimator_clone():
  function test_sparse_coder_parallel_mmap (line 586) | def test_sparse_coder_parallel_mmap():
  function test_sparse_coder_common_transformer (line 605) | def test_sparse_coder_common_transformer():
  function test_sparse_coder_deprecation (line 622) | def test_sparse_coder_deprecation():
  function test_sparse_coder_n_features_in (line 633) | def test_sparse_coder_n_features_in():
  function test_update_dict (line 639) | def test_update_dict():
  function test_warning_default_transform_alpha (line 663) | def test_warning_default_transform_alpha(Estimator):
  function test_get_feature_names_out (line 674) | def test_get_feature_names_out(estimator):

FILE: sklearn/decomposition/tests/test_factor_analysis.py
  function test_factor_analysis (line 20) | def test_factor_analysis():

FILE: sklearn/decomposition/tests/test_fastica.py
  function center_and_norm (line 19) | def center_and_norm(x, axis=-1):
  function test_gs (line 35) | def test_gs():
  function test_fastica_simple (line 55) | def test_fastica_simple(add_noise, seed):
  function test_fastica_nowhiten (line 142) | def test_fastica_nowhiten():
  function test_fastica_convergence_fail (line 153) | def test_fastica_convergence_fail():
  function test_non_square_fastica (line 184) | def test_non_square_fastica(add_noise):
  function test_fit_transform (line 229) | def test_fit_transform():
  function test_inverse_transform (line 267) | def test_inverse_transform(whiten, n_components, expected_mixing_shape):
  function test_fastica_errors (line 288) | def test_fastica_errors():
  function test_fastica_whiten_unit_variance (line 309) | def test_fastica_whiten_unit_variance():
  function test_fastica_whiten_default_value_deprecation (line 324) | def test_fastica_whiten_default_value_deprecation(ica):
  function test_fastica_whiten_backwards_compatibility (line 336) | def test_fastica_whiten_backwards_compatibility():
  function test_fastica_output_shape (line 375) | def test_fastica_output_shape(whiten, return_X_mean, return_n_iter):

FILE: sklearn/decomposition/tests/test_incremental_pca.py
  function test_incremental_pca (line 18) | def test_incremental_pca():
  function test_incremental_pca_sparse (line 48) | def test_incremental_pca_sparse(matrix_class):
  function test_incremental_pca_check_projection (line 86) | def test_incremental_pca_check_projection():
  function test_incremental_pca_inverse (line 107) | def test_incremental_pca_inverse():
  function test_incremental_pca_validation (line 123) | def test_incremental_pca_validation():
  function test_n_components_none (line 152) | def test_n_components_none():
  function test_incremental_pca_set_params (line 170) | def test_incremental_pca_set_params():
  function test_incremental_pca_num_features_change (line 193) | def test_incremental_pca_num_features_change():
  function test_incremental_pca_batch_signs (line 205) | def test_incremental_pca_batch_signs():
  function test_incremental_pca_batch_values (line 221) | def test_incremental_pca_batch_values():
  function test_incremental_pca_batch_rank (line 237) | def test_incremental_pca_batch_rank():
  function test_incremental_pca_partial_fit (line 253) | def test_incremental_pca_partial_fit():
  function test_incremental_pca_against_pca_iris (line 273) | def test_incremental_pca_against_pca_iris():
  function test_incremental_pca_against_pca_random_data (line 283) | def test_incremental_pca_against_pca_random_data():
  function test_explained_variances (line 296) | def test_explained_variances():
  function test_singular_values (line 315) | def test_singular_values():
  function test_whitening (line 372) | def test_whitening():
  function test_incremental_pca_partial_fit_float_division (line 393) | def test_incremental_pca_partial_fit_float_division():
  function test_incremental_pca_fit_overflow_error (line 418) | def test_incremental_pca_fit_overflow_error():
  function test_incremental_pca_feature_names_out (line 433) | def test_incremental_pca_feature_names_out():

FILE: sklearn/decomposition/tests/test_kernel_pca.py
  function test_kernel_pca (line 23) | def test_kernel_pca():
  function test_kernel_pca_invalid_solver (line 69) | def test_kernel_pca_invalid_solver():
  function test_kernel_pca_invalid_parameters (line 75) | def test_kernel_pca_invalid_parameters():
  function test_kernel_pca_consistent_transform (line 89) | def test_kernel_pca_consistent_transform():
  function test_kernel_pca_deterministic_output (line 108) | def test_kernel_pca_deterministic_output():
  function test_kernel_pca_sparse (line 125) | def test_kernel_pca_sparse():
  function test_kernel_pca_linear_kernel (line 164) | def test_kernel_pca_linear_kernel(solver, n_features):
  function test_kernel_pca_n_components (line 188) | def test_kernel_pca_n_components():
  function test_remove_zero_eig (line 206) | def test_remove_zero_eig():
  function test_leave_zero_eig (line 228) | def test_leave_zero_eig():
  function test_kernel_pca_precomputed (line 255) | def test_kernel_pca_precomputed():
  function test_kernel_pca_precomputed_non_symmetric (line 294) | def test_kernel_pca_precomputed_non_symmetric(solver):
  function test_kernel_pca_invalid_kernel (line 320) | def test_kernel_pca_invalid_kernel():
  function test_gridsearch_pipeline (line 332) | def test_gridsearch_pipeline():
  function test_gridsearch_pipeline_precomputed (line 347) | def test_gridsearch_pipeline_precomputed():
  function test_nested_circles (line 363) | def test_nested_circles():
  function test_kernel_conditioning (line 391) | def test_kernel_conditioning():
  function test_precomputed_kernel_not_psd (line 408) | def test_precomputed_kernel_not_psd(solver):
  function test_kernel_pca_solvers_equivalence (line 460) | def test_kernel_pca_solvers_equivalence(n_components):
  function test_kernel_pca_inverse_transform_reconstruction (line 496) | def test_kernel_pca_inverse_transform_reconstruction():
  function test_kernel_pca_raise_not_fitted_error (line 513) | def test_kernel_pca_raise_not_fitted_error():
  function test_32_64_decomposition_shape (line 521) | def test_32_64_decomposition_shape():
  function test_kernel_pcc_pairwise_is_deprecated (line 539) | def test_kernel_pcc_pairwise_is_deprecated():
  function test_kernel_pca_lambdas_deprecated (line 551) | def test_kernel_pca_lambdas_deprecated():
  function test_kernel_pca_alphas_deprecated (line 560) | def test_kernel_pca_alphas_deprecated():
  function test_kernel_pca_feature_names_out (line 568) | def test_kernel_pca_feature_names_out():

FILE: sklearn/decomposition/tests/test_nmf.py
  function test_convergence_warning (line 24) | def test_convergence_warning(solver):
  function test_initialize_nn_output (line 33) | def test_initialize_nn_output():
  function test_parameter_checking (line 42) | def test_parameter_checking():
  function test_initialize_close (line 85) | def test_initialize_close():
  function test_initialize_variants (line 97) | def test_initialize_variants():
  function test_nmf_fit_nn_output (line 117) | def test_nmf_fit_nn_output(solver, init, alpha_W, alpha_H):
  function test_nmf_fit_close (line 133) | def test_nmf_fit_close(solver):
  function test_nmf_transform (line 148) | def test_nmf_transform(solver):
  function test_nmf_transform_custom_init (line 164) | def test_nmf_transform_custom_init():
  function test_nmf_inverse_transform (line 179) | def test_nmf_inverse_transform(solver):
  function test_n_components_greater_n_features (line 195) | def test_n_components_greater_n_features():
  function test_nmf_sparse_input (line 205) | def test_nmf_sparse_input(solver, alpha_W, alpha_H):
  function test_nmf_sparse_transform (line 234) | def test_nmf_sparse_transform():
  function test_non_negative_factorization_consistency (line 254) | def test_non_negative_factorization_consistency(init, solver, alpha_W, a...
  function test_non_negative_factorization_checking (line 297) | def test_non_negative_factorization_checking():
  function _beta_divergence_dense (line 328) | def _beta_divergence_dense(X, W, H, beta):
  function test_beta_divergence (line 358) | def test_beta_divergence():
  function test_special_sparse_dot (line 381) | def test_special_sparse_dot():
  function test_nmf_multiplicative_update_sparse (line 409) | def test_nmf_multiplicative_update_sparse():
  function test_nmf_negative_beta_loss (line 487) | def test_nmf_negative_beta_loss():
  function test_nmf_regularization (line 524) | def test_nmf_regularization(solver):
  function test_nmf_decreasing (line 595) | def test_nmf_decreasing(solver):
  function test_nmf_underflow (line 647) | def test_nmf_underflow():
  function test_nmf_dtype_match (line 674) | def test_nmf_dtype_match(dtype_in, dtype_out, solver, alpha_W, alpha_H):
  function test_nmf_float32_float64_consistency (line 686) | def test_nmf_float32_float64_consistency(solver):
  function test_nmf_custom_init_dtype_error (line 699) | def test_nmf_custom_init_dtype_error():
  function test_feature_names_out (line 714) | def test_feature_names_out():

FILE: sklearn/decomposition/tests/test_online_lda.py
  function _build_sparse_mtx (line 26) | def _build_sparse_mtx():
  function test_lda_default_prior_params (line 37) | def test_lda_default_prior_params():
  function test_lda_fit_batch (line 54) | def test_lda_fit_batch():
  function test_lda_fit_online (line 73) | def test_lda_fit_online():
  function test_lda_partial_fit (line 93) | def test_lda_partial_fit():
  function test_lda_dense_input (line 113) | def test_lda_dense_input():
  function test_lda_transform (line 129) | def test_lda_transform():
  function test_lda_fit_transform (line 142) | def test_lda_fit_transform(method):
  function test_invalid_params (line 155) | def test_invalid_params():
  function test_lda_negative_input (line 171) | def test_lda_negative_input():
  function test_lda_no_component_error (line 180) | def test_lda_no_component_error():
  function test_lda_multi_jobs (line 196) | def test_lda_multi_jobs(method):
  function test_lda_partial_fit_multi_jobs (line 216) | def test_lda_partial_fit_multi_jobs():
  function test_lda_preplexity_mismatch (line 236) | def test_lda_preplexity_mismatch():
  function test_lda_perplexity (line 260) | def test_lda_perplexity(method):
  function test_lda_score (line 291) | def test_lda_score(method):
  function test_perplexity_input_format (line 317) | def test_perplexity_input_format():
  function test_lda_score_perplexity (line 334) | def test_lda_score_perplexity():
  function test_lda_fit_perplexity (line 348) | def test_lda_fit_perplexity():
  function test_lda_empty_docs (line 370) | def test_lda_empty_docs():
  function test_dirichlet_expectation (line 380) | def test_dirichlet_expectation():
  function check_verbosity (line 396) | def check_verbosity(verbose, evaluate_every, expected_lines, expected_pe...
  function test_verbosity (line 429) | def test_verbosity(verbose, evaluate_every, expected_lines, expected_per...
  function test_lda_feature_names_out (line 433) | def test_lda_feature_names_out():

FILE: sklearn/decomposition/tests/test_pca.py
  function test_pca (line 21) | def test_pca(svd_solver, n_components):
  function test_no_empty_slice_warning (line 41) | def test_no_empty_slice_warning():
  function test_whitening (line 54) | def test_whitening(solver, copy):
  function test_pca_explained_variance_equivalence_solver (line 108) | def test_pca_explained_variance_equivalence_solver(svd_solver):
  function test_pca_explained_variance_empirical (line 138) | def test_pca_explained_variance_empirical(X, svd_solver):
  function test_pca_singular_values_consistency (line 149) | def test_pca_singular_values_consistency(svd_solver):
  function test_pca_singular_values (line 164) | def test_pca_singular_values(svd_solver):
  function test_pca_check_projection (line 194) | def test_pca_check_projection(svd_solver):
  function test_pca_check_projection_list (line 209) | def test_pca_check_projection_list(svd_solver):
  function test_pca_inverse (line 221) | def test_pca_inverse(svd_solver, whiten):
  function test_pca_validation (line 267) | def test_pca_validation(svd_solver, data, n_components, err_msg):
  function test_n_components_none (line 303) | def test_n_components_none(data, solver, n_components_):
  function test_n_components_mle (line 310) | def test_n_components_mle(svd_solver):
  function test_n_components_mle_error (line 321) | def test_n_components_mle_error(svd_solver):
  function test_pca_dim (line 335) | def test_pca_dim():
  function test_infer_dim_1 (line 346) | def test_infer_dim_1():
  function test_infer_dim_2 (line 363) | def test_infer_dim_2():
  function test_infer_dim_3 (line 377) | def test_infer_dim_3():
  function test_infer_dim_by_explained_variance (line 398) | def test_infer_dim_by_explained_variance(X, n_components, n_components_v...
  function test_pca_score (line 406) | def test_pca_score(svd_solver):
  function test_pca_score3 (line 427) | def test_pca_score3():
  function test_pca_sanity_noise_variance (line 443) | def test_pca_sanity_noise_variance(svd_solver):
  function test_pca_score_consistency_solvers (line 455) | def test_pca_score_consistency_solvers(svd_solver):
  function test_pca_zero_noise_variance_edge_cases (line 467) | def test_pca_zero_noise_variance_edge_cases(svd_solver):
  function test_pca_svd_solver_auto (line 494) | def test_pca_svd_solver_auto(data, n_components, expected_solver):
  function test_pca_sparse_input (line 505) | def test_pca_sparse_input(svd_solver):
  function test_pca_bad_solver (line 515) | def test_pca_bad_solver():
  function test_pca_deterministic_output (line 523) | def test_pca_deterministic_output(svd_solver):
  function test_pca_dtype_preservation (line 535) | def test_pca_dtype_preservation(svd_solver):
  function check_pca_float_dtype_preservation (line 540) | def check_pca_float_dtype_preservation(svd_solver):
  function check_pca_int_dtype_upcast_to_double (line 559) | def check_pca_int_dtype_upcast_to_double(svd_solver):
  function test_pca_n_components_mostly_explained_variance_ratio (line 576) | def test_pca_n_components_mostly_explained_variance_ratio():
  function test_assess_dimension_bad_rank (line 588) | def test_assess_dimension_bad_rank():
  function test_small_eigenvalues_mle (line 597) | def test_small_eigenvalues_mle():
  function test_mle_redundant_data (line 610) | def test_mle_redundant_data():
  function test_fit_mle_too_few_samples (line 625) | def test_fit_mle_too_few_samples():
  function test_mle_simple_case (line 638) | def test_mle_simple_case():
  function test_assess_dimesion_rank_one (line 649) | def test_assess_dimesion_rank_one():
  function test_pca_randomized_svd_n_oversamples (line 662) | def test_pca_randomized_svd_n_oversamples():
  function test_pca_params_validation (line 703) | def test_pca_params_validation(params, err_type, err_msg):
  function test_feature_names_out (line 711) | def test_feature_names_out():

FILE: sklearn/decomposition/tests/test_sparse_pca.py
  function generate_toy_data (line 18) | def generate_toy_data(n_components, n_samples, image_size, random_state=...
  function test_correct_shapes (line 44) | def test_correct_shapes():
  function test_fit_transform (line 58) | def test_fit_transform():
  function test_fit_transform_parallel (line 72) | def test_fit_transform_parallel():
  function test_transform_nan (line 88) | def test_transform_nan():
  function test_fit_transform_tall (line 98) | def test_fit_transform_tall():
  function test_initialization (line 108) | def test_initialization():
  function test_mini_batch_correct_shapes (line 119) | def test_mini_batch_correct_shapes():
  function test_mini_batch_fit_transform (line 135) | def test_mini_batch_fit_transform():
  function test_scaling_fit_transform (line 166) | def test_scaling_fit_transform():
  function test_pca_vs_spca (line 176) | def test_pca_vs_spca():
  function test_spca_n_components_ (line 196) | def test_spca_n_components_(SPCA, n_components):
  function test_spca_feature_names_out (line 210) | def test_spca_feature_names_out(SPCA):

FILE: sklearn/decomposition/tests/test_truncated_svd.py
  function X_sparse (line 16) | def X_sparse():
  function test_solvers (line 26) | def test_solvers(X_sparse, solver, kind):
  function test_attributes (line 43) | def test_attributes(n_components, X_sparse):
  function test_too_many_components (line 51) | def test_too_many_components(algorithm, X_sparse):
  function test_sparse_formats (line 60) | def test_sparse_formats(fmt, X_sparse):
  function test_inverse_transform (line 71) | def test_inverse_transform(algo, X_sparse):
  function test_integers (line 80) | def test_integers(X_sparse):
  function test_explained_variance (line 91) | def test_explained_variance(X_sparse, kind, n_components, solver):
  function test_explained_variance_components_10_20 (line 114) | def test_explained_variance_components_10_20(X_sparse, kind, solver):
  function test_singular_values_consistency (line 133) | def test_singular_values_consistency(solver):
  function test_singular_values_expected (line 156) | def test_singular_values_expected(solver):
  function test_truncated_svd_eq_pca (line 176) | def test_truncated_svd_eq_pca(X_sparse):
  function test_fit_transform (line 200) | def test_fit_transform(X_sparse, algorithm, tol, kind):

FILE: sklearn/discriminant_analysis.py
  function _cov (line 30) | def _cov(X, shrinkage=None, covariance_estimator=None):
  function _class_means (line 96) | def _class_means(X, y):
  function _class_cov (line 120) | def _class_cov(X, y, priors, shrinkage=None, covariance_estimator=None):
  class LinearDiscriminantAnalysis (line 167) | class LinearDiscriminantAnalysis(
    method __init__ (line 312) | def __init__(
    method _solve_lsqr (line 330) | def _solve_lsqr(self, X, y, shrinkage, covariance_estimator):
    method _solve_eigen (line 386) | def _solve_eigen(self, X, y, shrinkage, covariance_estimator):
    method _solve_svd (line 452) | def _solve_svd(self, X, y):
    method fit (line 522) | def fit(self, X, y):
    method transform (line 619) | def transform(self, X):
    method predict_proba (line 646) | def predict_proba(self, X):
    method predict_log_proba (line 668) | def predict_log_proba(self, X):
    method decision_function (line 685) | def decision_function(self, X):
  class QuadraticDiscriminantAnalysis (line 709) | class QuadraticDiscriminantAnalysis(ClassifierMixin, BaseEstimator):
    method __init__ (line 810) | def __init__(
    method fit (line 818) | def fit(self, X, y):
    method _decision_function (line 893) | def _decision_function(self, X):
    method decision_function (line 909) | def decision_function(self, X):
    method predict (line 935) | def predict(self, X):
    method predict_proba (line 955) | def predict_proba(self, X):
    method p

[
  {
    "path": ".binder/postBuild",
    "chars": 1588,
    "preview": "#!/bin/bash\n\nset -e\n\n# This script is called in a binder context. When this script is called, we are\n# inside a git chec"
  },
  {
    "path": ".binder/requirements.txt",
    "chars": 147,
    "preview": "--extra-index https://pypi.anaconda.org/scipy-wheels-nightly/simple scikit-learn\n--pre\nmatplotlib\nscikit-image\npandas\nsp"
  },
  {
    "path": ".circleci/artifact_path",
    "chars": 20,
    "preview": "0/doc/_changed.html\n"
  },
  {
    "path": ".circleci/config.yml",
    "chars": 5116,
    "preview": "version: 2.1\n\njobs:\n  doc-min-dependencies:\n    docker:\n      - image: circleci/python:3.7.7-buster\n    environment:\n   "
  },
  {
    "path": ".codecov.yml",
    "chars": 921,
    "preview": "comment: false\n\ncoverage:\n  status:\n    project:\n      default:\n        # Commits pushed to main should not make the ove"
  },
  {
    "path": ".coveragerc",
    "chars": 150,
    "preview": "[run]\nbranch = True\nsource = sklearn\nparallel = True\nomit =\n    */sklearn/externals/*\n    */sklearn/_build_utils/*\n    *"
  },
  {
    "path": ".git-blame-ignore-revs",
    "chars": 690,
    "preview": "# Since git version 2.23, git-blame has a feature to ignore\n# certain commits.\n#\n# This file contains a list of commits "
  },
  {
    "path": ".gitattributes",
    "chars": 34,
    "preview": "/doc/whats_new/v*.rst merge=union\n"
  },
  {
    "path": ".github/FUNDING.yml",
    "chars": 687,
    "preview": "# These are supported funding model platforms\n\ngithub: # Replace with up to 4 GitHub Sponsors-enabled usernames e.g., [u"
  },
  {
    "path": ".github/ISSUE_TEMPLATE/bug_report.yml",
    "chars": 2559,
    "preview": "name: Bug Report\ndescription: Create a report to help us reproduce and correct the bug\nlabels: ['Bug: triage']\n\nbody:\n- "
  },
  {
    "path": ".github/ISSUE_TEMPLATE/config.yml",
    "chars": 843,
    "preview": "blank_issues_enabled: true\ncontact_links:\n  - name: Discussions\n    url: https://github.com/scikit-learn/scikit-learn/di"
  },
  {
    "path": ".github/ISSUE_TEMPLATE/doc_improvement.yml",
    "chars": 579,
    "preview": "name: Documentation improvement\ndescription: Create a report to help us improve the documentation. Alternatively you can"
  },
  {
    "path": ".github/ISSUE_TEMPLATE/feature_request.yml",
    "chars": 765,
    "preview": "name: Feature request\ndescription: Suggest a new algorithm, enhancement to an existing algorithm, etc.\nlabels: ['New Fea"
  },
  {
    "path": ".github/PULL_REQUEST_TEMPLATE.md",
    "chars": 1173,
    "preview": "<!--\nThanks for contributing a pull request! Please ensure you have taken a look at\nthe contribution guidelines: https:/"
  },
  {
    "path": ".github/labeler-file-extensions.yml",
    "chars": 151,
    "preview": "cython:\n- sklearn/**/*.pyx\n- sklearn/**/*.pxd\n- sklearn/**/*.pxi\n# Tempita templates\n- sklearn/**/*.pyx.tp\n- sklearn/**/"
  },
  {
    "path": ".github/labeler-module.yml",
    "chars": 1249,
    "preview": "module:cluster:\n- sklearn/cluster/**/*\n\nmodule:common:\n- sklearn/common/**/*\n\nmodule:compose:\n- sklearn/compose/**/*\n\nmo"
  },
  {
    "path": ".github/scripts/label_title_regex.py",
    "chars": 638,
    "preview": "\"\"\"Labels PRs based on title. Must be run in a github action with the\npull_request_target event.\"\"\"\nfrom github import G"
  },
  {
    "path": ".github/workflows/assign.yml",
    "chars": 800,
    "preview": "\nname: Assign\non:\n  issue_comment:\n    types: created\n\njobs:\n  one:\n    runs-on: ubuntu-latest\n    if: >-\n      (github."
  },
  {
    "path": ".github/workflows/check-changelog.yml",
    "chars": 2960,
    "preview": "name: Check Changelog\n# This check makes sure that the changelog is properly updated\n# when a PR introduces a change in "
  },
  {
    "path": ".github/workflows/check-manifest.yml",
    "chars": 480,
    "preview": "name: \"Check Manifest\"\n\non:\n  schedule:\n    - cron: '0 0 * * *'\n\njobs:\n  check:\n    runs-on: ubuntu-latest\n    steps:\n  "
  },
  {
    "path": ".github/workflows/labeler-module.yml",
    "chars": 699,
    "preview": "name: \"Pull Request Labeler\"\non: pull_request_target\n\njobs:\n  triage:\n    runs-on: ubuntu-latest\n    steps:\n    - uses: "
  },
  {
    "path": ".github/workflows/labeler-title-regex.yml",
    "chars": 522,
    "preview": "name: Pull Request Regex Title Labeler\non:\n  pull_request_target:\n    types: [opened, edited]\n\npermissions:\n  contents: "
  },
  {
    "path": ".github/workflows/publish_pypi.yml",
    "chars": 1586,
    "preview": "name: Publish to Pypi\non:\n  workflow_dispatch:\n    inputs:\n      version:\n        description: 'Version upload to pypi'\n"
  },
  {
    "path": ".github/workflows/twitter.yml",
    "chars": 840,
    "preview": "# Tweet the URL of a commit on @sklearn_commits whenever a push event\n# happens on the main branch\nname: Twitter Push No"
  },
  {
    "path": ".github/workflows/unassign.yml",
    "chars": 550,
    "preview": "name: Unassign\n#Runs when a contributor has unassigned themselves from the issue and adds 'help wanted'\non:\n  issues:\n  "
  },
  {
    "path": ".github/workflows/wheels.yml",
    "chars": 5834,
    "preview": "# Workflow to build and test wheels\nname: Wheel builder\n\non:\n  schedule:\n    # Nightly build at 3:42 A.M.\n    - cron: \"4"
  },
  {
    "path": ".gitignore",
    "chars": 1055,
    "preview": "*.pyc\n*.so\n*.pyd\n*~\n.#*\n*.lprof\n*.swp\n*.swo\n.DS_Store\nbuild\nsklearn/datasets/__config__.py\nsklearn/**/*.html\n\ndist/\nMANI"
  },
  {
    "path": ".mailmap",
    "chars": 7262,
    "preview": "Alexandre Gramfort <alexandre.gramfort@inria.fr> <alexandre.gramfort@gmail.com>\nAlexandre Gramfort <alexandre.gramfort@i"
  },
  {
    "path": ".pre-commit-config.yaml",
    "chars": 547,
    "preview": "repos:\n-   repo: https://github.com/pre-commit/pre-commit-hooks\n    rev: v2.3.0\n    hooks:\n    -   id: check-yaml\n    - "
  },
  {
    "path": ".travis.yml",
    "chars": 2460,
    "preview": "# Make it explicit that we favor the\n# new container-based Travis workers\nlanguage: python\ndist: xenial\n\ncache:\n  apt: t"
  },
  {
    "path": "CODE_OF_CONDUCT.md",
    "chars": 645,
    "preview": "# Code of Conduct\n\nWe are a community based on openness, as well as friendly and didactic discussions.\n\nWe aspire to tre"
  },
  {
    "path": "CONTRIBUTING.md",
    "chars": 2109,
    "preview": "\nContributing to scikit-learn\n============================\n\nThe latest contributing guide is available in the repository"
  },
  {
    "path": "COPYING",
    "chars": 1532,
    "preview": "BSD 3-Clause License\n\nCopyright (c) 2007-2021 The scikit-learn developers.\nAll rights reserved.\n\nRedistribution and use "
  },
  {
    "path": "MANIFEST.in",
    "chars": 941,
    "preview": "include *.rst\nrecursive-include doc *\nrecursive-include examples *\nrecursive-include sklearn *.c *.h *.pyx *.pxd *.pxi *"
  },
  {
    "path": "Makefile",
    "chars": 1634,
    "preview": "# simple makefile to simplify repetitive build env management tasks under posix\n\n# caution: testing won't work on window"
  },
  {
    "path": "README.rst",
    "chars": 6972,
    "preview": ".. -*- mode: rst -*-\n\n|Azure|_ |Travis|_ |Codecov|_ |CircleCI|_ |Nightly wheels|_ |Black|_ |PythonVersion|_ |PyPi|_ |DOI"
  },
  {
    "path": "SECURITY.md",
    "chars": 556,
    "preview": "# Security Policy\n\n## Supported Versions\n\n| Version   | Supported          |\n| --------- | ------------------ |\n| 1.0.1 "
  },
  {
    "path": "asv_benchmarks/.gitignore",
    "chars": 66,
    "preview": "*__pycache__*\nenv/\nhtml/\nresults/\nscikit-learn/\nbenchmarks/cache/\n"
  },
  {
    "path": "asv_benchmarks/asv.conf.json",
    "chars": 6732,
    "preview": "{\n    // The version of the config file format.  Do not change, unless\n    // you know what you are doing.\n    \"version\""
  },
  {
    "path": "asv_benchmarks/benchmarks/__init__.py",
    "chars": 49,
    "preview": "\"\"\"Benchmark suite for scikit-learn using ASV\"\"\"\n"
  },
  {
    "path": "asv_benchmarks/benchmarks/cluster.py",
    "chars": 2925,
    "preview": "from sklearn.cluster import KMeans, MiniBatchKMeans\n\nfrom .common import Benchmark, Estimator, Predictor, Transformer\nfr"
  },
  {
    "path": "asv_benchmarks/benchmarks/common.py",
    "chars": 7341,
    "preview": "import os\nimport json\nimport timeit\nimport pickle\nimport itertools\nfrom abc import ABC, abstractmethod\nfrom pathlib impo"
  },
  {
    "path": "asv_benchmarks/benchmarks/config.json",
    "chars": 1544,
    "preview": "{\n    // \"regular\": Bencharks are run on small to medium datasets. Each benchmark\n    //            is run multiple time"
  },
  {
    "path": "asv_benchmarks/benchmarks/datasets.py",
    "chars": 5144,
    "preview": "import numpy as np\nimport scipy.sparse as sp\nfrom joblib import Memory\nfrom pathlib import Path\n\nfrom sklearn.decomposit"
  },
  {
    "path": "asv_benchmarks/benchmarks/decomposition.py",
    "chars": 2375,
    "preview": "from sklearn.decomposition import PCA, DictionaryLearning, MiniBatchDictionaryLearning\n\nfrom .common import Benchmark, E"
  },
  {
    "path": "asv_benchmarks/benchmarks/ensemble.py",
    "chars": 2995,
    "preview": "from sklearn.ensemble import (\n    RandomForestClassifier,\n    GradientBoostingClassifier,\n    HistGradientBoostingClass"
  },
  {
    "path": "asv_benchmarks/benchmarks/linear_model.py",
    "chars": 6549,
    "preview": "from sklearn.linear_model import (\n    LogisticRegression,\n    Ridge,\n    ElasticNet,\n    Lasso,\n    LinearRegression,\n "
  },
  {
    "path": "asv_benchmarks/benchmarks/manifold.py",
    "chars": 820,
    "preview": "from sklearn.manifold import TSNE\n\nfrom .common import Benchmark, Estimator\nfrom .datasets import _digits_dataset\n\n\nclas"
  },
  {
    "path": "asv_benchmarks/benchmarks/metrics.py",
    "chars": 1363,
    "preview": "from sklearn.metrics.pairwise import pairwise_distances\n\nfrom .common import Benchmark\nfrom .datasets import _random_dat"
  },
  {
    "path": "asv_benchmarks/benchmarks/model_selection.py",
    "chars": 2371,
    "preview": "from sklearn.ensemble import RandomForestClassifier\nfrom sklearn.model_selection import GridSearchCV, cross_val_score\n\nf"
  },
  {
    "path": "asv_benchmarks/benchmarks/neighbors.py",
    "chars": 1140,
    "preview": "from sklearn.neighbors import KNeighborsClassifier\n\nfrom .common import Benchmark, Estimator, Predictor\nfrom .datasets i"
  },
  {
    "path": "asv_benchmarks/benchmarks/svm.py",
    "chars": 762,
    "preview": "from sklearn.svm import SVC\n\nfrom .common import Benchmark, Estimator, Predictor\nfrom .datasets import _synth_classifica"
  },
  {
    "path": "asv_benchmarks/benchmarks/utils.py",
    "chars": 1310,
    "preview": "import numpy as np\n\nfrom sklearn.metrics import balanced_accuracy_score, r2_score\n\n\ndef neg_mean_inertia(X, labels, cent"
  },
  {
    "path": "azure-pipelines.yml",
    "chars": 8673,
    "preview": "# Adapted from https://github.com/pandas-dev/pandas/blob/master/azure-pipelines.yml\nschedules:\n- cron: \"30 2 * * *\"\n  di"
  },
  {
    "path": "benchmarks/.gitignore",
    "chars": 41,
    "preview": "/bhtsne\n*.npy\n*.json\n/mnist_tsne_output/\n"
  },
  {
    "path": "benchmarks/bench_20newsgroups.py",
    "chars": 3165,
    "preview": "from time import time\nimport argparse\nimport numpy as np\n\nfrom sklearn.dummy import DummyClassifier\n\nfrom sklearn.datase"
  },
  {
    "path": "benchmarks/bench_covertype.py",
    "chars": 7421,
    "preview": "\"\"\"\n===========================\nCovertype dataset benchmark\n===========================\n\nBenchmark stochastic gradient d"
  },
  {
    "path": "benchmarks/bench_feature_expansions.py",
    "chars": 1773,
    "preview": "import matplotlib.pyplot as plt\nimport numpy as np\nimport scipy.sparse as sparse\nfrom sklearn.preprocessing import Polyn"
  },
  {
    "path": "benchmarks/bench_glm.py",
    "chars": 1479,
    "preview": "\"\"\"\nA comparison of different methods in GLM\n\nData comes from a random square matrix.\n\n\"\"\"\nfrom datetime import datetime"
  },
  {
    "path": "benchmarks/bench_glmnet.py",
    "chars": 3965,
    "preview": "\"\"\"\nTo run this, you'll need to have installed.\n\n  * glmnet-python\n  * scikit-learn (of course)\n\nDoes two benchmarks\n\nFi"
  },
  {
    "path": "benchmarks/bench_hist_gradient_boosting.py",
    "chars": 9687,
    "preview": "from time import time\nimport argparse\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom sklearn.model_selection i"
  },
  {
    "path": "benchmarks/bench_hist_gradient_boosting_adult.py",
    "chars": 2998,
    "preview": "import argparse\nfrom time import time\n\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.datasets import"
  },
  {
    "path": "benchmarks/bench_hist_gradient_boosting_categorical_only.py",
    "chars": 2621,
    "preview": "import argparse\nfrom time import time\n\nfrom sklearn.preprocessing import KBinsDiscretizer\nfrom sklearn.datasets import m"
  },
  {
    "path": "benchmarks/bench_hist_gradient_boosting_higgsboson.py",
    "chars": 3815,
    "preview": "from urllib.request import urlretrieve\nimport os\nfrom gzip import GzipFile\nfrom time import time\nimport argparse\n\nimport"
  },
  {
    "path": "benchmarks/bench_hist_gradient_boosting_threading.py",
    "chars": 11094,
    "preview": "from time import time\nimport argparse\nimport os\nfrom pprint import pprint\n\nimport numpy as np\nfrom threadpoolctl import "
  },
  {
    "path": "benchmarks/bench_isolation_forest.py",
    "chars": 5463,
    "preview": "\"\"\"\n==========================================\nIsolationForest benchmark\n==========================================\nA te"
  },
  {
    "path": "benchmarks/bench_isotonic.py",
    "chars": 3274,
    "preview": "\"\"\"\nBenchmarks of isotonic regression performance.\n\nWe generate a synthetic dataset of size 10^n, for n in [min, max], a"
  },
  {
    "path": "benchmarks/bench_kernel_pca_solvers_time_vs_n_components.py",
    "chars": 5463,
    "preview": "\"\"\"\n=============================================================\nKernel PCA Solvers comparison benchmark: time vs n_com"
  },
  {
    "path": "benchmarks/bench_kernel_pca_solvers_time_vs_n_samples.py",
    "chars": 5731,
    "preview": "\"\"\"\n==========================================================\nKernel PCA Solvers comparison benchmark: time vs n_sample"
  },
  {
    "path": "benchmarks/bench_lasso.py",
    "chars": 3144,
    "preview": "\"\"\"\nBenchmarks of Lasso vs LassoLars\n\nFirst, we fix a training set and increase the number of\nsamples. Then we plot the "
  },
  {
    "path": "benchmarks/bench_lof.py",
    "chars": 3491,
    "preview": "\"\"\"\n============================\nLocalOutlierFactor benchmark\n============================\n\nA test of LocalOutlierFactor"
  },
  {
    "path": "benchmarks/bench_mnist.py",
    "chars": 7032,
    "preview": "\"\"\"\n=======================\nMNIST dataset benchmark\n=======================\n\nBenchmark on the MNIST dataset.  The datase"
  },
  {
    "path": "benchmarks/bench_multilabel_metrics.py",
    "chars": 6796,
    "preview": "#!/usr/bin/env python\n\"\"\"\nA comparison of multilabel target formats and metrics over them\n\"\"\"\n\nfrom timeit import timeit"
  },
  {
    "path": "benchmarks/bench_online_ocsvm.py",
    "chars": 9422,
    "preview": "\"\"\"\n=====================================\nSGDOneClassSVM benchmark\n=====================================\nThis benchmark "
  },
  {
    "path": "benchmarks/bench_plot_fastkmeans.py",
    "chars": 4420,
    "preview": "from collections import defaultdict\nfrom time import time\n\nimport numpy as np\nfrom numpy import random as nr\n\nfrom sklea"
  },
  {
    "path": "benchmarks/bench_plot_hierarchical.py",
    "chars": 2556,
    "preview": "from collections import defaultdict\nfrom time import time\n\nimport numpy as np\nfrom numpy import random as nr\n\nfrom sklea"
  },
  {
    "path": "benchmarks/bench_plot_incremental_pca.py",
    "chars": 5559,
    "preview": "\"\"\"\n========================\nIncrementalPCA benchmark\n========================\n\nBenchmarks for IncrementalPCA\n\n\"\"\"\n\nimpo"
  },
  {
    "path": "benchmarks/bench_plot_lasso_path.py",
    "chars": 3942,
    "preview": "\"\"\"Benchmarks of Lasso regularization path computation using Lars and CD\n\nThe input data is mostly low rank but is a fat"
  },
  {
    "path": "benchmarks/bench_plot_neighbors.py",
    "chars": 5721,
    "preview": "\"\"\"\nPlot the scaling of the nearest neighbors algorithms with k, D, and N\n\"\"\"\nfrom time import time\n\nimport numpy as np\n"
  },
  {
    "path": "benchmarks/bench_plot_nmf.py",
    "chars": 15607,
    "preview": "\"\"\"\nBenchmarks of Non-Negative Matrix Factorization\n\"\"\"\n# Authors: Tom Dupre la Tour (benchmark)\n#          Chih-Jen Lin"
  },
  {
    "path": "benchmarks/bench_plot_omp_lars.py",
    "chars": 4413,
    "preview": "\"\"\"Benchmarks of orthogonal matching pursuit (:ref:`OMP`) versus least angle\nregression (:ref:`least_angle_regression`)\n"
  },
  {
    "path": "benchmarks/bench_plot_parallel_pairwise.py",
    "chars": 1272,
    "preview": "# Author: Mathieu Blondel <mathieu@mblondel.org>\n# License: BSD 3 clause\nimport time\n\nimport matplotlib.pyplot as plt\n\nf"
  },
  {
    "path": "benchmarks/bench_plot_polynomial_kernel_approximation.py",
    "chars": 5995,
    "preview": "\"\"\"\n========================================================================\nBenchmark for explicit feature map approxim"
  },
  {
    "path": "benchmarks/bench_plot_randomized_svd.py",
    "chars": 17940,
    "preview": "\"\"\"\nBenchmarks on the power iterations phase in randomized SVD.\n\nWe test on various synthetic and real datasets the effe"
  },
  {
    "path": "benchmarks/bench_plot_svd.py",
    "chars": 2749,
    "preview": "\"\"\"Benchmarks of Singular Value Decomposition (Exact and Approximate)\n\nThe data is mostly low rank but is a fat infinite"
  },
  {
    "path": "benchmarks/bench_plot_ward.py",
    "chars": 1270,
    "preview": "\"\"\"\nBenchmark scikit-learn's Ward implement compared to SciPy's\n\"\"\"\n\nimport time\n\nimport numpy as np\nfrom scipy.cluster "
  },
  {
    "path": "benchmarks/bench_random_projections.py",
    "chars": 8572,
    "preview": "\"\"\"\n===========================\nRandom projection benchmark\n===========================\n\nBenchmarks for random projectio"
  },
  {
    "path": "benchmarks/bench_rcv1_logreg_convergence.py",
    "chars": 7808,
    "preview": "# Authors: Tom Dupre la Tour <tom.dupre-la-tour@m4x.org>\n#          Olivier Grisel <olivier.grisel@ensta.org>\n#\n# Licens"
  },
  {
    "path": "benchmarks/bench_saga.py",
    "chars": 10887,
    "preview": "\"\"\"Author: Arthur Mensch, Nelle Varoquaux\n\nBenchmarks of sklearn SAGA vs lightning SAGA vs Liblinear. Shows the gain\nin "
  },
  {
    "path": "benchmarks/bench_sample_without_replacement.py",
    "chars": 7311,
    "preview": "\"\"\"\nBenchmarks for sampling without replacement of integer.\n\n\"\"\"\nimport gc\nimport sys\nimport optparse\nfrom datetime impo"
  },
  {
    "path": "benchmarks/bench_sgd_regression.py",
    "chars": 5340,
    "preview": "# Author: Peter Prettenhofer <peter.prettenhofer@gmail.com>\n# License: BSD 3 clause\n\nimport numpy as np\nimport matplotli"
  },
  {
    "path": "benchmarks/bench_sparsify.py",
    "chars": 3360,
    "preview": "\"\"\"\nBenchmark SGD prediction time with dense/sparse coefficients.\n\nInvoke with\n-----------\n\n$ kernprof.py -l sparsity_be"
  },
  {
    "path": "benchmarks/bench_text_vectorizers.py",
    "chars": 1920,
    "preview": "\"\"\"\n\nTo run this benchmark, you will need,\n\n * scikit-learn\n * pandas\n * memory_profiler\n * psutil (optional, but recomm"
  },
  {
    "path": "benchmarks/bench_tree.py",
    "chars": 3625,
    "preview": "\"\"\"\nTo run this, you'll need to have installed.\n\n  * scikit-learn\n\nDoes two benchmarks\n\nFirst, we fix a training set, in"
  },
  {
    "path": "benchmarks/bench_tsne_mnist.py",
    "chars": 6385,
    "preview": "\"\"\"\n=============================\nMNIST dataset T-SNE benchmark\n=============================\n\n\"\"\"\n\n# License: BSD 3 cla"
  },
  {
    "path": "benchmarks/plot_tsne_mnist.py",
    "chars": 858,
    "preview": "import matplotlib.pyplot as plt\nimport numpy as np\nimport os.path as op\n\nimport argparse\n\n\nLOG_DIR = \"mnist_tsne_output\""
  },
  {
    "path": "build_tools/Makefile",
    "chars": 77,
    "preview": "# Makefile for maintenance tools\n\nauthors:\n\tpython generate_authors_table.py\n"
  },
  {
    "path": "build_tools/azure/install.sh",
    "chars": 7221,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\nUNAMESTR=`uname`\n\nif [[ \"$DISTRIB\" == \"conda-mamba-pypy3\" ]]; then\n    # condaforge/mambafor"
  },
  {
    "path": "build_tools/azure/install_win.sh",
    "chars": 816,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\nif [[ \"$PYTHON_ARCH\" == \"64\" ]]; then\n    conda create -n $VIRTUALENV -q -y python=$PYTHON_V"
  },
  {
    "path": "build_tools/azure/posix-docker.yml",
    "chars": 2883,
    "preview": "parameters:\n  name: ''\n  vmImage: ''\n  matrix: []\n  dependsOn: []\n  condition: ne(variables['Build.Reason'], 'Schedule')"
  },
  {
    "path": "build_tools/azure/posix.yml",
    "chars": 3695,
    "preview": "parameters:\n  name: ''\n  vmImage: ''\n  matrix: []\n  dependsOn: []\n  condition: ''\n\njobs:\n- job: ${{ parameters.name }}\n "
  },
  {
    "path": "build_tools/azure/test_docs.sh",
    "chars": 272,
    "preview": "#!/bin/bash\n\nset -e\n\nif [[ \"$DISTRIB\" =~ ^conda.* ]]; then\n    source activate $VIRTUALENV\nelif [[ \"$DISTRIB\" == \"ubuntu"
  },
  {
    "path": "build_tools/azure/test_docstring.sh",
    "chars": 296,
    "preview": "#!/bin/bash\n\nset -e\n\nif [[ \"$DISTRIB\" =~ ^conda.* ]]; then\n    source activate $VIRTUALENV\nelif [[ \"$DISTRIB\" == \"ubuntu"
  },
  {
    "path": "build_tools/azure/test_pytest_soft_dependency.sh",
    "chars": 710,
    "preview": "#!/bin/bash\n\nset -e\n\n# called when DISTRIB==\"conda\"\nsource activate $VIRTUALENV\nconda remove -y py pytest || pip uninsta"
  },
  {
    "path": "build_tools/azure/test_script.sh",
    "chars": 1930,
    "preview": "#!/bin/bash\n\nset -e\n\nif [[ \"$DISTRIB\" =~ ^conda.* ]]; then\n    source activate $VIRTUALENV\nelif [[ \"$DISTRIB\" == \"ubuntu"
  },
  {
    "path": "build_tools/azure/upload_codecov.sh",
    "chars": 439,
    "preview": "#!/bin/bash\n\nset -e\n\n# called when COVERAGE==\"true\" and DISTRIB==\"conda\"\nexport PATH=$HOME/miniconda3/bin:$PATH\nsource a"
  },
  {
    "path": "build_tools/azure/windows.yml",
    "chars": 1660,
    "preview": "\nparameters:\n  name: ''\n  vmImage: ''\n  matrix: []\n  dependsOn: []\n  condition: ne(variables['Build.Reason'], 'Schedule'"
  },
  {
    "path": "build_tools/circle/build_doc.sh",
    "chars": 9472,
    "preview": "#!/usr/bin/env bash\nset -x\nset -e\n\n# Decide what kind of documentation build to run, and run it.\n#\n# If the last commit "
  },
  {
    "path": "build_tools/circle/build_test_arm.sh",
    "chars": 2715,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\nUNAMESTR=`uname`\nN_CORES=`nproc --all`\n\n\nsetup_ccache() {\n    echo \"Setting up ccache\"\n    m"
  },
  {
    "path": "build_tools/circle/build_test_pypy.sh",
    "chars": 1156,
    "preview": "#!/usr/bin/env bash\nset -x\nset -e\n\n# System build tools\napt-get -yq update\napt-get -yq install wget bzip2 build-essentia"
  },
  {
    "path": "build_tools/circle/checkout_merge_commit.sh",
    "chars": 920,
    "preview": "#!/bin/bash\n\n\n# Add `main` branch to the update list.\n# Otherwise CircleCI will give us a cached one.\nFETCH_REFS=\"+main:"
  },
  {
    "path": "build_tools/circle/linting.sh",
    "chars": 6943,
    "preview": "#!/bin/bash\n\n# This script is used in CircleCI to check that PRs do not add obvious\n# flake8 violations. It relies on tw"
  },
  {
    "path": "build_tools/circle/list_versions.py",
    "chars": 3731,
    "preview": "#!/usr/bin/env python3\n\n# List all available versions of the documentation\nimport json\nimport re\nimport sys\n\nfrom distut"
  },
  {
    "path": "build_tools/circle/push_doc.sh",
    "chars": 1611,
    "preview": "#!/bin/bash\n# This script is meant to be called in the \"deploy\" step defined in\n# circle.yml. See https://circleci.com/d"
  },
  {
    "path": "build_tools/codespell_ignore_words.txt",
    "chars": 232,
    "preview": "aggresive\naline\nba\nbasf\nboun\nbre\ncach\ncomplies\ncoo\ncopys\ndeine\ndidi\nfeld\nfo\nfpr\nfro\nfwe\ngool\nhart\nhist\nines\ninout\nist\nja"
  },
  {
    "path": "build_tools/generate_authors_table.py",
    "chars": 5459,
    "preview": "\"\"\"\nThis script generates an html table of contributors, with names and avatars.\nThe list is generated from scikit-learn"
  },
  {
    "path": "build_tools/github/Windows",
    "chars": 417,
    "preview": "# Get the Python version of the base image from a build argument\nARG PYTHON_VERSION\nFROM winamd64/python:$PYTHON_VERSION"
  },
  {
    "path": "build_tools/github/build_minimal_windows_image.sh",
    "chars": 944,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\nPYTHON_VERSION=$1\nBITNESS=$2\n\nif [[ \"$BITNESS\" == \"32\" ]]; then\n    # 32-bit architectures a"
  },
  {
    "path": "build_tools/github/build_source.sh",
    "chars": 391,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\n# Move up two levels to create the virtual\n# environment outside of the source folder\ncd ../"
  },
  {
    "path": "build_tools/github/build_wheels.sh",
    "chars": 1352,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\n# OpenMP is not present on macOS by default\nif [[ \"$RUNNER_OS\" == \"macOS\" ]]; then\n    # Mak"
  },
  {
    "path": "build_tools/github/check_build_trigger.sh",
    "chars": 278,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\nCOMMIT_MSG=$(git log --no-merges -1 --oneline)\n\n# The commit marker \"[cd build]\" will trigge"
  },
  {
    "path": "build_tools/github/check_wheels.py",
    "chars": 1324,
    "preview": "\"\"\"Checks that dist/* contains the number of wheels built from the\n.github/workflows/wheels.yml config.\"\"\"\nimport yaml\nf"
  },
  {
    "path": "build_tools/github/repair_windows_wheels.sh",
    "chars": 354,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\nWHEEL=$1\nDEST_DIR=$2\nBITNESS=$3\n\n# By default, the Windows wheels are not repaired.\n# In thi"
  },
  {
    "path": "build_tools/github/test_source.sh",
    "chars": 359,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\ncd ../../\n\npython -m venv test_env\nsource test_env/bin/activate\n\npython -m pip install sciki"
  },
  {
    "path": "build_tools/github/test_wheels.sh",
    "chars": 436,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\nif [[ \"$OSTYPE\" != \"linux-gnu\" ]]; then\n    # The Linux test environment is run in a Docker "
  },
  {
    "path": "build_tools/github/test_windows_wheels.sh",
    "chars": 713,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\nPYTHON_VERSION=$1\nBITNESS=$2\n\nif [[ \"$BITNESS\" == \"32\" ]]; then\n    # 32-bit architectures u"
  },
  {
    "path": "build_tools/github/upload_anaconda.sh",
    "chars": 654,
    "preview": "#!/bin/bash\n\nset -e\nset -x\n\nif [ \"$GITHUB_EVENT_NAME\" == \"schedule\" ]; then\n    ANACONDA_ORG=\"scipy-wheels-nightly\"\n    "
  },
  {
    "path": "build_tools/github/vendor.py",
    "chars": 5765,
    "preview": "\"\"\"Embed vcomp140.dll, vcruntime140.dll and vcruntime140_1.dll.\n\nNote that vcruntime140_1.dll is only required (and avai"
  },
  {
    "path": "build_tools/shared.sh",
    "chars": 470,
    "preview": "get_dep() {\n    package=\"$1\"\n    version=\"$2\"\n    if [[ \"$version\" == \"none\" ]]; then\n        # do not install with none"
  },
  {
    "path": "build_tools/travis/after_success.sh",
    "chars": 1402,
    "preview": "#!/bin/bash\n\n# This script is meant to be called by the \"after_success\" step\n# defined in \".travis.yml\". In particular, "
  },
  {
    "path": "build_tools/travis/install.sh",
    "chars": 371,
    "preview": "#!/bin/bash\n\n# This script is meant to be called by the \"install\" step\n# defined in the \".travis.yml\" file. In particula"
  },
  {
    "path": "build_tools/travis/install_main.sh",
    "chars": 1850,
    "preview": "#!/bin/bash\n\n# Travis clone \"scikit-learn/scikit-learn\" repository into\n# a local repository. We use a cached directory "
  },
  {
    "path": "build_tools/travis/install_wheels.sh",
    "chars": 141,
    "preview": "#!/bin/bash\n\npython -m pip install cibuildwheel || travis_terminate $?\npython -m cibuildwheel --output-dir wheelhouse ||"
  },
  {
    "path": "build_tools/travis/script.sh",
    "chars": 496,
    "preview": "#!/bin/bash\n\n# This script is meant to be called by the \"script\" step defined\n# in the \".travis.yml\" file. While this st"
  },
  {
    "path": "build_tools/travis/test_docs.sh",
    "chars": 157,
    "preview": "#!/bin/bash\n\nset -e\n\nif [[ $TRAVIS_CPU_ARCH != arm64 ]]; then\n    # Faster run of the documentation tests\n    PYTEST=\"py"
  },
  {
    "path": "build_tools/travis/test_script.sh",
    "chars": 944,
    "preview": "#!/bin/bash\n\nset -e\n\npython --version\npython -c \"import numpy; print(f'numpy {numpy.__version__}')\"\npython -c \"import sc"
  },
  {
    "path": "build_tools/travis/test_wheels.sh",
    "chars": 375,
    "preview": "#!/bin/bash\n\npip install --upgrade pip || travis_terminate $?\npip install pytest pytest-xdist || travis_terminate $?\n\n# "
  },
  {
    "path": "conftest.py",
    "chars": 388,
    "preview": "# Even if empty this file is useful so that when running from the root folder\n# ./sklearn is added to sys.path by pytest"
  },
  {
    "path": "doc/Makefile",
    "chars": 4211,
    "preview": "# Makefile for Sphinx documentation\n#\n\n# You can set these variables from the command line.\nSPHINXOPTS    = -j auto\nSPHI"
  },
  {
    "path": "doc/README.md",
    "chars": 253,
    "preview": "# Documentation for scikit-learn\n\nThis directory contains the full manual and website as displayed at\nhttp://scikit-lear"
  },
  {
    "path": "doc/about.rst",
    "chars": 15512,
    "preview": ".. _about:\n\nAbout us\n========\n\nHistory\n-------\n\nThis project was started in 2007 as a Google Summer of Code project by\nD"
  },
  {
    "path": "doc/authors.rst",
    "chars": 4209,
    "preview": ".. raw :: html\n\n    <!-- Generated by generate_authors_table.py -->\n    <div class=\"sk-authors-container\">\n    <style>\n "
  },
  {
    "path": "doc/authors_emeritus.rst",
    "chars": 574,
    "preview": "- Mathieu Blondel\n- Matthieu Brucher\n- Lars Buitinck\n- David Cournapeau\n- Noel Dawe\n- Vincent Dubourg\n- Edouard Duchesna"
  },
  {
    "path": "doc/binder/requirements.txt",
    "chars": 255,
    "preview": "# A binder requirement file is required by sphinx-gallery.\n# We don't really need one since our binder requirement file "
  },
  {
    "path": "doc/common_pitfalls.rst",
    "chars": 25003,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\n.. include:: includes/big_toc_css.rst\n\n.. _common_pitfalls:\n\n=="
  },
  {
    "path": "doc/communication_team.rst",
    "chars": 545,
    "preview": ".. raw :: html\n\n    <!-- Generated by generate_authors_table.py -->\n    <div class=\"sk-authors-container\">\n    <style>\n "
  },
  {
    "path": "doc/computing/computational_performance.rst",
    "chars": 17322,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\n.. _computational_performance:\n\n.. currentmodule:: sklearn\n\nCom"
  },
  {
    "path": "doc/computing/parallelism.rst",
    "chars": 8388,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\nParallelism, resource management, and configuration\n==========="
  },
  {
    "path": "doc/computing/scaling_strategies.rst",
    "chars": 6368,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\n.. _scaling_strategies:\n\nStrategies to scale computationally: b"
  },
  {
    "path": "doc/computing.rst",
    "chars": 313,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\n============================\nComputing with scikit-learn\n======"
  },
  {
    "path": "doc/conf.py",
    "chars": 17544,
    "preview": "# -*- coding: utf-8 -*-\n#\n# scikit-learn documentation build configuration file, created by\n# sphinx-quickstart on Fri J"
  },
  {
    "path": "doc/conftest.py",
    "chars": 5191,
    "preview": "import os\nfrom os.path import exists\nfrom os.path import join\nfrom os import environ\nimport warnings\n\nfrom sklearn.utils"
  },
  {
    "path": "doc/contents.rst",
    "chars": 406,
    "preview": ".. include:: includes/big_toc_css.rst\n.. include:: tune_toc.rst\n\n.. Places global toc into the sidebar\n\n:globalsidebarto"
  },
  {
    "path": "doc/data_transforms.rst",
    "chars": 1381,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\n.. include:: includes/big_toc_css.rst\n\n.. _data-transforms:\n\nDa"
  },
  {
    "path": "doc/datasets/loading_other_datasets.rst",
    "chars": 10530,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\n.. _loading_other_datasets:\n\nLoading other datasets\n==========="
  },
  {
    "path": "doc/datasets/real_world.rst",
    "chars": 917,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\n.. _real_world_datasets:\n\nReal world datasets\n================="
  },
  {
    "path": "doc/datasets/sample_generators.rst",
    "chars": 4095,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\n.. _sample_generators:\n\nGenerated datasets\n==================\n\n"
  },
  {
    "path": "doc/datasets/toy_dataset.rst",
    "chars": 1057,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\n.. _toy_datasets:\n\nToy datasets\n============\n\n.. currentmodule:"
  },
  {
    "path": "doc/datasets.rst",
    "chars": 2657,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\n.. include:: includes/big_toc_css.rst\n\n.. _datasets:\n\n========="
  },
  {
    "path": "doc/developers/advanced_installation.rst",
    "chars": 16978,
    "preview": "\n.. _advanced-installation:\n\n.. include:: ../min_dependency_substitutions.rst\n\n========================================="
  },
  {
    "path": "doc/developers/bug_triaging.rst",
    "chars": 6273,
    "preview": ".. _bug_triaging:\n\nBug triaging and issue curation\n===============================\n\nThe `issue tracker <https://github.c"
  },
  {
    "path": "doc/developers/contributing.rst",
    "chars": 56857,
    "preview": ".. _contributing:\n\n============\nContributing\n============\n\n.. currentmodule:: sklearn\n\nThis project is a community effor"
  },
  {
    "path": "doc/developers/develop.rst",
    "chars": 32990,
    "preview": ".. _develop:\n\n==================================\nDeveloping scikit-learn estimators\n==================================\n\n"
  },
  {
    "path": "doc/developers/index.rst",
    "chars": 350,
    "preview": ".. Places parent toc into the sidebar\n\n:parenttoc: True\n\n.. _developers_guide:\n\n=================\nDeveloper's Guide\n===="
  },
  {
    "path": "doc/developers/maintainer.rst",
    "chars": 18041,
    "preview": "Maintainer / core-developer information\n========================================\n\n\nReleasing\n---------\n\nThis section is "
  },
  {
    "path": "doc/developers/performance.rst",
    "chars": 17241,
    "preview": ".. _performance-howto:\n\n=========================\nHow to optimize for speed\n=========================\n\nThe following giv"
  },
  {
    "path": "doc/developers/plotting.rst",
    "chars": 4372,
    "preview": ".. _plotting_api:\n\n================================\nDeveloping with the Plotting API\n================================\n\nS"
  },
  {
    "path": "doc/developers/tips.rst",
    "chars": 14578,
    "preview": ".. _developers-tips:\n\n===========================\nDevelopers' Tips and Tricks\n===========================\n\nProductivity "
  },
  {
    "path": "doc/developers/utilities.rst",
    "chars": 8863,
    "preview": ".. _developers-utils:\n\n========================\nUtilities for Developers\n========================\n\nScikit-learn contains"
  },
  {
    "path": "doc/faq.rst",
    "chars": 21280,
    "preview": ".. _faq:\n\n===========================\nFrequently Asked Questions\n===========================\n\n.. currentmodule:: sklearn"
  },
  {
    "path": "doc/getting_started.rst",
    "chars": 10277,
    "preview": "Getting Started\n===============\n\nThe purpose of this guide is to illustrate some of the main features that\n``scikit-lear"
  },
  {
    "path": "doc/glossary.rst",
    "chars": 86061,
    "preview": ".. currentmodule:: sklearn\n\n.. _glossary:\n\n=========================================\nGlossary of Common Terms and API El"
  },
  {
    "path": "doc/governance.rst",
    "chars": 8691,
    "preview": ".. _governance:\n\n===========================================\nScikit-learn governance and decision-making\n==============="
  },
  {
    "path": "doc/includes/big_toc_css.rst",
    "chars": 730,
    "preview": "..  \n    File to ..include in a document with a big table of content, to give\n    it 'style'\n\n.. raw:: html\n\n  <style ty"
  },
  {
    "path": "doc/includes/bigger_toc_css.rst",
    "chars": 1035,
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    "preview": ".. _biclustering:\n\n============\nBiclustering\n============\n\nBiclustering can be performed with the module\n:mod:`sklearn.c"
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    "preview": ".. _api_ref:\n\n=============\nAPI Reference\n=============\n\nThis is the class and function reference of scikit-learn. Pleas"
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    "preview": ".. _kernel_ridge:\n\n===========================\nKernel ridge regression\n===========================\n\n.. currentmodule:: s"
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]

// ... and 1069 more files (download for full content)