Skip to main content

Permutation and drop-column importance for scikit-learn random forests and other models

Project description

A library that provides feature importances, based upon the permutation importance strategy, for general scikit-learn models and implementations specifically for random forest out-of-bag scores. Built by Terence Parr and Kerem Turgutlu. See <a href=”http://explained.ai/rf-importance/index.html”>Beware Default Random Forest Importances</a> for a deeper discussion of the issues surrounding feature importances in random forests.

Project details


Download files

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

Source Distribution

rfpimp-1.2.1.tar.gz (9.1 kB view details)

Uploaded Source

File details

Details for the file rfpimp-1.2.1.tar.gz.

File metadata

  • Download URL: rfpimp-1.2.1.tar.gz
  • Upload date:
  • Size: 9.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: Python-urllib/3.6

File hashes

Hashes for rfpimp-1.2.1.tar.gz
Algorithm Hash digest
SHA256 ba3b985732dabaed4955e19d88753f6924b4db3fc1e8fd674b6766ee9509bb85
MD5 e10f38e1554b4994b3c995f9972f2fa5
BLAKE2b-256 38cf8c5ebc4b67bd2885918d5954547b046ab2a4019ea0cd2b6204fb448aed66

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page