# metric-learn: Metric Learning Algorithms in Python

arXiv: https://arxiv.org/abs/1908.04710 · HTML: https://mlsanity.com/paper/1908.04710/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Aug 2019.

## Built on by (most cited first, 11 of 11)

- [Does It Capture STEL? A Modular, Similarity-based Linguistic Style Evaluation Framework](https://mlsanity.com/paper/2109.04817/) (2021)
- [Spectral, Probabilistic, and Deep Metric Learning: Tutorial and Survey](https://mlsanity.com/paper/2201.09267/) (2022)
- [Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling](https://mlsanity.com/paper/2107.11972/) (2021)
- [Robust Geometric Metric Learning](https://mlsanity.com/paper/2202.11550/) (2022)
- [Can an unsupervised clustering algorithm reproduce a categorization system?](https://mlsanity.com/paper/2408.10340/) (2024)
- [Metric Learning in Multilingual Sentence Similarity Measurement for Document Alignment](https://mlsanity.com/paper/2108.09495/) (2021)
- [Metric Learning Improves the Ability of Combinatorial Coverage Metrics to Anticipate Classification Error](https://mlsanity.com/paper/2302.14616/) (2023)
- [Improved Aircraft Environmental Impact Segmentation via Metric Learning](https://mlsanity.com/paper/2306.13830/) (2023)
- [Gender mobility in the labor market with skills-based matching models](https://mlsanity.com/paper/2307.08368/) (2023)
- [Supervised Quadratic Feature Analysis: Information Geometry Approach for Dimensionality Reduction](https://mlsanity.com/paper/2502.00168/) (2025)
- [Global Ground Metric Learning with Applications to scRNA data](https://mlsanity.com/paper/2506.15383/) (2025)

## Abstract (arXiv)

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.