About us#


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.


Refers to GitHub contributors page.

Citing imbalanced-learn#

If you use imbalanced-learn in a scientific publication, we would appreciate citations to the following paper:

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}