Imbalanced-learn

Changelog

Bug fixes

- Fix a bug in [classification_report_imbalanced](https://imbalanced-learn.org/stable/references/generated/imblearn.metrics.classification_report_imbalanced.html#imblearn.metrics.classification_report_imbalanced) where the parameter `target_names` was not taken into account when `output_dict=True`. [989](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/989) by [AYY7](https://github.com/AYY7).

- [SMOTENC](https://imbalanced-learn.org/stable/references/generated/imblearn.over_sampling.SMOTENC.html#imblearn.over_sampling.SMOTENC) now handles mix types of data type such as bool and `pd.CategoricalDtype` by delegating the conversion to scikit-learn encoder. [1002](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/1002) by [Guillaume Lemaitre](https://github.com/glemaitre).

- Handle sparse matrices in [SMOTEN](https://imbalanced-learn.org/stable/references/generated/imblearn.over_sampling.SMOTEN.html#imblearn.over_sampling.SMOTEN) and raise a warning since it requires a conversion to dense matrices. [1003](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/1003) by [Guillaume Lemaitre](https://github.com/glemaitre).

- Remove spurious warning raised when minority class get over-sampled more than the number of sample in the majority class. [1007](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/1007) by [Guillaume Lemaitre](https://github.com/glemaitre).

Compatibility

- Maintenance release for being compatible with scikit-learn >= 1.3.0. [999](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/999) by [Guillaume Lemaitre](https://github.com/glemaitre).

Deprecation

- The fitted attribute `ohe_` in [SMOTENC](https://imbalanced-learn.org/stable/references/generated/imblearn.over_sampling.SMOTENC.html#imblearn.over_sampling.SMOTENC) is deprecated and will be removed in version 0.13. Use `categorical_encoder_` instead. [1000](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/1000) by [Guillaume Lemaitre](https://github.com/glemaitre).

- The default of the parameters `sampling_strategy` and replacement will change in [BalancedRandomForestClassifier](https://imbalanced-learn.org/stable/references/generated/imblearn.ensemble.BalancedRandomForestClassifier.html#imblearn.ensemble.BalancedRandomForestClassifier) to follow the implementation of the original paper. This changes will take effect in version 0.13. [1006](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/1006) by [Guillaume Lemaitre](https://github.com/glemaitre).

Enhancements

- [SMOTENC](https://imbalanced-learn.org/stable/references/generated/imblearn.over_sampling.SMOTENC.html#imblearn.over_sampling.SMOTENC) now accepts a parameter `categorical_encoder` allowing to specify a `OneHotEncoder` with custom parameters. [1000](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/1000) by [Guillaume Lemaitre](https://github.com/glemaitre).

- [SMOTEN](https://imbalanced-learn.org/stable/references/generated/imblearn.over_sampling.SMOTEN.html#imblearn.over_sampling.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](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/1001) by [Guillaume Lemaitre](https://github.com/glemaitre).

- [RandomUnderSampler](https://imbalanced-learn.org/stable/references/generated/imblearn.under_sampling.RandomUnderSampler.html#imblearn.under_sampling.RandomUnderSampler) and [RandomOverSampler](https://imbalanced-learn.org/stable/references/generated/imblearn.over_sampling.RandomOverSampler.html#imblearn.over_sampling.RandomOverSampler) (when `shrinkage` is not `None`) now accept any data types and will not attempt any data conversion. [1004](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/1004) by [Guillaume Lemaitre](https://github.com/glemaitre).

- [SMOTENC](https://imbalanced-learn.org/stable/references/generated/imblearn.over_sampling.SMOTENC.html#imblearn.over_sampling.SMOTENC) now support passing array-like of `str` when passing the `categorical_features` parameter. [1008](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/1008) by :user`Guillaume Lemaitre <glemaitre>`.

- [SMOTENC](https://imbalanced-learn.org/stable/references/generated/imblearn.over_sampling.SMOTENC.html#imblearn.over_sampling.SMOTENC) now support automatic categorical inference when `categorical_features` is set to `"auto"`. [1009](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/1009) by :user`Guillaume Lemaitre <glemaitre>`.

Changelog
========

Bug fixes
---------

- Fix a regression in over-sampler where the string `minority` was rejected as an unvalid sampling strategy. 964 by Prakhyath07.

Changelog
========

Bug fixes
---------

- Make sure that Substitution is working with `python -OO` that replaces __doc__ by None. [953](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/953) bu [Guillaume Lemaitre](https://github.com/glemaitre).

Compatibility
-------------

- Maintenance release for being compatible with scikit-learn >= 1.0.2. [946](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/946), [#947](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/947), [#949](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/949) by [Guillaume Lemaitre](https://github.com/glemaitre).
- Add support for automatic parameters validation as in scikit-learn >= 1.2. [955](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/955) by [Guillaume Lemaitre](https://github.com/glemaitre).
- Add support for `feature_names_in_` as well as `get_feature_names_out` for all samplers. [959](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/959) by [Guillaume Lemaitre](https://github.com/glemaitre).

Deprecation
------------

- The parameter `n_jobs` has been deprecated from the classes [ADASYN](https://imbalanced-learn.org/dev/references/generated/imblearn.over_sampling.ADASYN.html#imblearn.over_sampling.ADASYN), [BorderlineSMOTE](https://imbalanced-learn.org/dev/references/generated/imblearn.over_sampling.BorderlineSMOTE.html#imblearn.over_sampling.BorderlineSMOTE), [SMOTE](https://imbalanced-learn.org/dev/references/generated/imblearn.over_sampling.SMOTE.html#imblearn.over_sampling.SMOTE), [SMOTENC](https://imbalanced-learn.org/dev/references/generated/imblearn.over_sampling.SMOTENC.html#imblearn.over_sampling.SMOTENC), [SMOTEN](https://imbalanced-learn.org/dev/references/generated/imblearn.over_sampling.SMOTEN.html#imblearn.over_sampling.SMOTEN), and [SVMSMOTE](https://imbalanced-learn.org/dev/references/generated/imblearn.over_sampling.SVMSMOTE.html#imblearn.over_sampling.SVMSMOTE). Instead, pass a nearest neighbors estimator where n_jobs is set. [887](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/887) by [Guillaume Lemaitre](https://github.com/glemaitre).
- The parameter `base_estimator` is deprecated and will be removed in version 0.12. It is impacted the following classes: [BalancedBaggingClassifier](https://imbalanced-learn.org/dev/references/generated/imblearn.ensemble.BalancedBaggingClassifier.html#imblearn.ensemble.BalancedBaggingClassifier), [EasyEnsembleClassifier](https://imbalanced-learn.org/dev/references/generated/imblearn.ensemble.EasyEnsembleClassifier.html#imblearn.ensemble.EasyEnsembleClassifier), [RUSBoostClassifier](https://imbalanced-learn.org/dev/references/generated/imblearn.ensemble.RUSBoostClassifier.html#imblearn.ensemble.RUSBoostClassifier). [946](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/946) by [Guillaume Lemaitre](https://github.com/glemaitre).

Enhancements
---------------

- Add support to accept compatible NearestNeighbors objects by only duck-typing. For instance, it allows to accept cuML instances. [858](https://github.com/scikit-learn-contrib/imbalanced-learn/pull/858) by [NV-jpt](https://github.com/NV-jpt) and [Guillaume Lemaitre](https://github.com/glemaitre).

September 29, 2021

Maintenance

Make imbalanced-learn compatible with scikit-learn 1.0. 864 by Guillaume Lemaitre.