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-1.3.5.tar.gz (10.3 kB view details)

Uploaded Source

File details

Details for the file rfpimp-1.3.5.tar.gz.

File metadata

  • Download URL: rfpimp-1.3.5.tar.gz
  • Upload date:
  • Size: 10.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: Python-urllib/3.7

File hashes

Hashes for rfpimp-1.3.5.tar.gz
Algorithm Hash digest
SHA256 8c373c3ee41880a7f516b5a7814230c7c02fee2b877b5f70e1648c443d5a0fde
MD5 4727f64558577151d5d8d263c7aa9f00
BLAKE2b-256 3605ce8f1d3a035a4ddda3c888af945908e9f61cbec32f73148fc8e788a8632a

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