  imbalanced-ensemble, abbreviated as imbens, is an open-source Python toolbox
for leveraging the power of ensemble learning to address the class imbalance
problem. It provides standard implementations of popular ensemble imbalanced
learning (EIL) methods with extended features and utility functions. These
ensemble methods include resampling-based, e.g., under/over-sampling, and
reweighting-based, e.g., cost-sensitive learning. Beyond the implementation, we
empower EIL algorithms with new functionalities like customizable resampling
scheduler and verbose logging, thus enabling more flexible training and
evaluating strategies. The package was developed under a simple,
well-documented API design that follows scikit-learn for increased ease of use.
imbens is released under the MIT open-source license and can be installed from
Python Package Index (PyPI) or
https://github.com/ZhiningLiu1998/imbalanced-ensemble.
