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``imbalanced-learn`` is a set of python methods to deal with imbalanced
datset in machine learning and pattern recognition.

Subpackages
-----------
combine
    Module which provides methods based on over-sampling and under-sampling.
ensemble
    Module which provides methods generating an ensemble of
    under-sampled subsets.
exceptions
    Module including custom warnings and error clases used across
    imbalanced-learn.
keras
    Module which provides custom generator, layers for deep learning using
    keras.
metrics
    Module which provides metrics to quantified the classification performance
    with imbalanced dataset.
over_sampling
    Module which provides methods to over-sample a dataset.
tensorflow
    Module which provides custom generator, layers for deep learning using
    tensorflow.
under-sampling
    Module which provides methods to under-sample a dataset.
utils
    Module including various utilities.
pipeline
    Module which allowing to create pipeline with scikit-learn estimators.
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   r   Ú_versionr   Úbaser   Zutils._show_versionsr   Ú
ModuleTyper   Úglobalsr*   Ú__all__r   r   r   r   Ú<module>!   s6   
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