About us¶
History¶
Development lead¶
The project started in August 2014 by Fernando Nogueira and focused on SMOTE implementation. Together with Guillaume Lemaitre, Dayvid Victor, and Christos Aridas, additional under-sampling and over-sampling methods have been implemented as well as major changes in the API to be fully compatible with scikit-learn.
Citing imbalanced-learn¶
If you use imbalanced-learn in a scientific publication, we would appreciate citations to the following paper:
@article{JMLR:v18:16-365,
author = {Guillaume Lema{{\^i}}tre and Fernando Nogueira and Christos K. Aridas},
title = {Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning},
journal = {Journal of Machine Learning Research},
year = {2017},
volume = {18},
number = {17},
pages = {1-5},
url = {http://jmlr.org/papers/v18/16-365.html}
}