Abstract
This paper presents multi-imbalance, an open-source Python library, which equips the constantly growing Python community with appropriate tools to deal with multi-class imbalanced problems. It follows the code conventions of sklearn package. It provides implementations of state-of-the-art binary decomposition techniques, ensembles, as well as both novel and classic re-sampling approaches for multi-class imbalanced classification. For demonstration and documentation, consult the project web page: www.cs.put.poznan.pl/mlango/multiimbalance.php.
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Notes
- 1.
An extended version of this example is available at multi-imbalance Github repository https://github.com/damian-horna/multi-imbalance/blob/master/examples/use_case.ipynb.
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This research was supported by PUT Statutory Funds.
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Grycza, J., Horna, D., Klimczak, H., Lango, M., Pluciński, K., Stefanowski, J. (2021). multi-imbalance: Open Source Python Toolbox for Multi-class Imbalanced Classification. In: Dong, Y., Ifrim, G., Mladenić, D., Saunders, C., Van Hoecke, S. (eds) Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track. ECML PKDD 2020. Lecture Notes in Computer Science(), vol 12461. Springer, Cham. https://doi.org/10.1007/978-3-030-67670-4_36
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DOI: https://doi.org/10.1007/978-3-030-67670-4_36
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