This is a pre-production deployment of Warehouse, however changes made here WILL affect the production instance of PyPI.
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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 History

1.1.0

This version

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1.0.3

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1.0.2

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1.0.1

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TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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Download Files

Download Files

TODO: Brief introduction on what you do with files - including link to relevant help section.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
featureimpact-1.1.0.tar.gz (5.5 kB) Copy SHA256 Checksum SHA256 Source Aug 17, 2014

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