Skip to main content
Help improve PyPI by participating in a 5-minute user interface survey!

Compute the statistical impact of features given a scikit-learn estimator

Project Description

This package let’s you compute the statistical impact of features given a scikit-learn estimator. The computation is based on the mean variation of the difference between quantile and original predictions. The impact is reliable for regressors and binary classifiers.

Currently, all features must consist of pure-numerical, non-categorical values.

featureimpact is being developed by Christian Blume. Contact Christian at chr.blume@gmail.com for any questions or comments.

Note: In order to run the examples you’ll need scikit-learn and matplotlib installed in addition to this package and its regular dependencies.

Release history Release notifications

This version
History Node

1.1.0

History Node

1.0.3

History Node

1.0.2

History Node

1.0.1

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
featureimpact-1.1.0.tar.gz (5.5 kB) Copy SHA256 hash SHA256 Source None Aug 17, 2014

Supported by

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