metric-learn: Metric Learning Algorithms in Python

William de Vazelhes, CJ Carey, Yuan Tang, Nathalie Vauquier, Aurélien Bellet
8/13/2019
cs.LGstat.ML

Official code: scikit-learn-contrib/metric-learn (1,431 stars, MIT, last commit 2026-03-19).

Abstract

metric-learn is an open source Python package implementing supervised and weakly-supervised distance metric learning algorithms. As part of scikit-learn-contrib, it provides a unified interface compatible with scikit-learn which allows to easily perform cross-validation, model selection, and pipelining with other machine learning estimators. metric-learn is thoroughly tested and available on PyPi under the MIT licence.

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Code Implementations(1)

scikit-learn-contrib/metric-learnOfficial100%
MIT

Metric learning algorithms in Python

1,431232PythonNov 2, 20137 months agoMIT
machine-learningmetric-learningpythonscikit-learn

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Cite this paper

@article{vazelhes2019metriclearn,
  title  = {metric-learn: Metric Learning Algorithms in Python},
  author = {William de Vazelhes and CJ Carey and Yuan Tang and Nathalie Vauquier and Aurélien Bellet},
  year   = {2019},
  eprint = {1908.04710},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1908.04710}
}

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