scikit-learn/examples/preprocessing
Christian Lorentzen 811b588360
ENH change default scoring to log loss in LogisticRegressionCV (#33333)
Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
Co-authored-by: Omar Salman <omar.salman@arbisoft.com>
2026-03-16 14:56:30 +05:00
..
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 ENH change default scoring to log loss in LogisticRegressionCV (#33333) 2026-03-16 14:56:30 +05:00
plot_target_encoder.py DOC: Clarify recommended usage of fit_transform() vs fit().transform() in TargetEncoder (#32347) 2025-10-23 17:15:35 +02:00
plot_target_encoder_cross_val.py MNT Deprecate `shuffle` and `random_state` params from `TargetEncoder` (#33453) 2026-03-10 18:10:10 +01:00

README.txt

.. _preprocessing_examples:

Preprocessing
-------------

Examples concerning the :mod:`sklearn.preprocessing` module.