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2020 JMLR JMLR 2020

metric-learn: Metric Learning Algorithms in Python

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 license. [abs] [ pdf ][ bib ] [ code ] © JMLR 2020. (edit, beta)

🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio

Authors

William de Vazelhes , CJ Carey , Yuan Tang , Nathalie Vauquier , Aurélien Bellet

Topics

Machine Learning > Core Methods > Metric Learning Machine Learning > Core Methods > Embedding Learning Machine Learning > Learning Types > Weakly Supervised Learning

Keywords

metric learning weakly supervised learning distance metric learning distance metric
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