metric-learn is an open-source Python library offering efficient implementations of several popular supervised and weakly-supervised metric learning algorithms. Fully compatible with scikit-learn, it enables users to integrate metric learning methods into pipelines, model selection, and other scikit-learn workflows. It's designed for researchers, practitioners, and machine learning engineers needing distance metric learning tools for clustering, classification, and regression tasks.
Visit metric-learn's official website for product details and getting started.
Comprehensive API reference and usage examples for the metric-learn library.
A collection of example use cases and tutorials demonstrating how to use the metric-learn library.
Engage with other users and contributors of metric-learn for support and discussions.