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Arturo Amor 3f110690d0
DOC Rework outlier detection estimators example (#25878) 
Co-authored-by: ArturoAmorQ <arturo.amor-quiroz@polytechnique.edu>
Co-authored-by: Tim Head <betatim@gmail.com>
Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
 		2023-09-11 18:26:17 +02:00
..
README.txt DOC Make release highlights the first gallery section (#16952) 2020-04-27 11:23:15 -04:00
plot_anomaly_comparison.py MNT add isort to ruff's rules (#26649) 2023-06-21 17:50:07 +02:00
plot_display_object_visualization.py MAINT Fix typos found by codespell (#26852) 2023-07-18 10:20:40 +02:00
plot_estimator_representation.py MNT add isort to ruff's rules (#26649) 2023-06-21 17:50:07 +02:00
plot_isotonic_regression.py MNT add isort to ruff's rules (#26649) 2023-06-21 17:50:07 +02:00
plot_johnson_lindenstrauss_bound.py MNT add isort to ruff's rules (#26649) 2023-06-21 17:50:07 +02:00
plot_kernel_approximation.py DOC fix random_state in example for reproducibility cont'd (#27238) 2023-09-07 12:01:54 +02:00
plot_kernel_ridge_regression.py MNT add isort to ruff's rules (#26649) 2023-06-21 17:50:07 +02:00
plot_metadata_routing.py MNT (SLEP6) remove other_params from provess_routing (#26909) 2023-07-27 17:43:45 +00:00
plot_multilabel.py MNT add isort to ruff's rules (#26649) 2023-06-21 17:50:07 +02:00
plot_multioutput_face_completion.py MNT add isort to ruff's rules (#26649) 2023-06-21 17:50:07 +02:00
plot_outlier_detection_bench.py DOC Rework outlier detection estimators example (#25878) 2023-09-11 18:26:17 +02:00
plot_partial_dependence_visualization_api.py MNT add isort to ruff's rules (#26649) 2023-06-21 17:50:07 +02:00
plot_pipeline_display.py MNT add isort to ruff's rules (#26649) 2023-06-21 17:50:07 +02:00
plot_roc_curve_visualization_api.py MNT add isort to ruff's rules (#26649) 2023-06-21 17:50:07 +02:00
plot_set_output.py MNT add isort to ruff's rules (#26649) 2023-06-21 17:50:07 +02:00

README.txt 

.. _miscellaneous_examples:

Miscellaneous
-------------

Miscellaneous and introductory examples for scikit-learn.