# metric-learn: Metric Learning in Python¶

metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised metric learning algorithms. As part of scikit-learn-contrib, the API of metric-learn is compatible with scikit-learn, the leading library for machine learning in Python. This allows to use all the scikit-learn routines (for pipelining, model selection, etc) with metric learning algorithms through a unified interface.

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

metric-learn: Metric Learning Algorithms in Python, de Vazelhes et al., Journal of Machine Learning Research, 21(138):1-6, 2020.

Bibtex entry:

@article{metric-learn,
title = {metric-learn: {M}etric {L}earning {A}lgorithms in {P}ython},
author = {{de Vazelhes}, William and {Carey}, CJ and {Tang}, Yuan and
{Vauquier}, Nathalie and {Bellet}, Aur{\'e}lien},
journal = {Journal of Machine Learning Research},
year = {2020},
volume = {21},
number = {138},
pages = {1--6}
}