Bump imbalanced-learn from 0.8.1 to 0.11.0

[dependabot]

Bumps imbalanced-learn from 0.8.1 to 0.11.0.

Release notes

Sourced from imbalanced-learn's releases.

imbalanced-learn 0.11.0

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.

Compatibility

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

Deprecation

• 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.

Enhancements

• 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>.

imbalanced-learn 0.10.1

Changelog

Bug fixes

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

imbalanced-learn 0.10.0

Changelog

Bug fixes

... (truncated)

Commits

• 20ba698 DOC fix merge conflict
• 3fbcda6 bumpversion 0.11.0
• 3a7633d MAINT Add fixture for dataset generation in common tests (#932)
• 5be5670 FIX do not ignore target_names when output_dict=True in `classification_r...
• e9d120a ENH add auto inference based on pd.CategoricalDtype in SMOTENC (#1009)
• 704d106 ENH support array-like of str for categorical_features in SMOTENC (#1008)
• b468f7f FIX remove spurious warning raised when over-sampling the minority class (#1007)
• f14033b DOC fix AttributeError in Sequential object - predict_proba (#993)
• 2b126e3 API change default of replacement and sampling_strategy in BRF (#1006)
• 92b5305 ENH allow any dtype in input from RandomSampler (#1004)
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