Skip to main content

Calculate various metrics relevant for learning to rank algorithms.

Project description

Introduction

This package contains functions for calculating various metrics relevant for learning to rank systems such as recommender systems.

IMPORTANT: This project is still in its very early stages. Results should be taken with a grain of salt.

scikit-learn-like APIs

This package aims to provide APIs that are familiar if you are used to working with scikit-learn.

Supported metrics

  • Recall@k
  • Bag Recall@k
  • Mean Rank Percentile
  • NDCG

Project details


Release history Release notifications

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
rankmetrics-1.0.0-py2.py3-none-any.whl (5.6 kB) Copy SHA256 hash SHA256 Wheel py2.py3
rankmetrics-1.0.0.tar.gz (4.8 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page