recmetrics
A Python library providing evaluation metrics and diagnostic tools for recommender systems.
What is recmetrics?
recmetrics is a Python library that provides a collection of evaluation metrics and diagnostic tools specifically for recommender systems. It helps data scientists and machine learning engineers measure the performance, coverage, novelty, and personalization of recommendation algorithms to build more effective and unbiased systems.
Data scientists, machine learning engineers, and researchers working on recommender systems who need standardized metrics to evaluate model performance and diagnose issues like popularity bias or low coverage.
Developers choose recmetrics because it consolidates essential recommender system metrics into one open-source Python library, saving time from manual implementation and offering practical visualizations for model diagnostics directly informed by real-world industry use.
Overview
A library of metrics for evaluating recommender systems
Use Cases
Best For
- Evaluating collaborative filtering models for popularity bias
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