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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
rfpimp-1.2.2.tar.gz
(9.1 kB
view details)
File details
Details for the file rfpimp-1.2.2.tar.gz.
File metadata
- Download URL: rfpimp-1.2.2.tar.gz
- Upload date:
- Size: 9.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: Python-urllib/3.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
56ae40c952c2806a8a003c2558c92f46ca6cdb0594e4a385581e527938b8cf5c
|
|
| MD5 |
81cce3a5288e498fc62e22bad746bc42
|
|
| BLAKE2b-256 |
084ce3276342682c4a239a47b6dde8491cff0826f6879d63d0a1cd87d581ddee
|