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DOC: mention EasyEnsemble in BalancedBaggingClassifier #448

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DOC: mention EasyEnsemble in BalancedBaggingClassifier #448

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7 changes: 6 additions & 1 deletion imblearn/ensemble/classifier.py
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Expand Up @@ -23,7 +23,8 @@
sampling_strategy=BaseUnderSampler._sampling_strategy_docstring,
random_state=_random_state_docstring)
class BalancedBaggingClassifier(BaggingClassifier):
"""A Bagging classifier with additional balancing.
"""A Bagging classifier with additional balancing. It is similar to
``EasyEnsemble`` [6]_.

This implementation of Bagging is similar to the scikit-learn
implementation. It includes an additional step to balance the training set
Expand Down Expand Up @@ -146,6 +147,10 @@ class BalancedBaggingClassifier(BaggingClassifier):
.. [5] Chen, Chao, Andy Liaw, and Leo Breiman. "Using random forest to
learn imbalanced data." University of California, Berkeley 110,
2004.
.. [6] X. Y. Liu, J. Wu and Z. H. Zhou, "Exploratory Undersampling for
Class-Imbalance Learning," in IEEE Transactions on Systems, Man, and
Cybernetics, Part B (Cybernetics), vol. 39, no. 2, pp. 539-550,
April 2009.

Examples
--------
Expand Down