Changelog

Bug fixes

Fix a bug in classification_report_imbalanced where the parameter target_names was not taken into account when output_dict=True. #989 by AYY7.
SMOTENC now handles mix types of data type such as bool and pd.CategoricalDtype by delegating the conversion to scikit-learn encoder. #1002 by Guillaume Lemaitre.
Handle sparse matrices in SMOTEN and raise a warning since it requires a conversion to dense matrices. #1003 by Guillaume Lemaitre.
Remove spurious warning raised when minority class get over-sampled more than the number of sample in the majority class. #1007 by Guillaume Lemaitre.

Maintenance release for being compatible with scikit-learn >= 1.3.0. #999 by Guillaume Lemaitre.

The fitted attribute ohe_ in SMOTENC is deprecated and will be removed in version 0.13. Use categorical_encoder_ instead. #1000 by Guillaume Lemaitre.
The default of the parameters sampling_strategy and replacement will change in BalancedRandomForestClassifier to follow the implementation of the original paper. This changes will take effect in version 0.13. #1006 by Guillaume Lemaitre.

SMOTENC now accepts a parameter categorical_encoder allowing to specify a OneHotEncoder with custom parameters. #1000 by Guillaume Lemaitre.
SMOTEN now accepts a parameter categorical_encoder allowing to specify a OrdinalEncoder with custom parameters. A new fitted parameter categorical_encoder_ is exposed to access the fitted encoder. #1001 by Guillaume Lemaitre.
RandomUnderSampler and RandomOverSampler (when shrinkage is not None) now accept any data types and will not attempt any data conversion. #1004 by Guillaume Lemaitre.
SMOTENC now support passing array-like of str when passing the categorical_features parameter. #1008 by :userGuillaume Lemaitre <glemaitre>.
SMOTENC now support automatic categorical inference when categorical_features is set to "auto". #1009 by :userGuillaume Lemaitre <glemaitre>.