⚠️There's a newer version (0.11.4) of this package.Take me there.
iml (version 0.11.0)
Interpretable Machine Learning
Description
Interpretability methods to analyze the behavior and
predictions of any machine learning model. Implemented methods are:
Feature importance described by Fisher et al. (2018)
, accumulated local effects plots described by Apley
(2018) , partial dependence plots described by
Friedman (2001) , individual conditional
expectation ('ice') plots described by Goldstein et al. (2013)
, local models (variant of 'lime')
described by Ribeiro et. al (2016) , the Shapley
Value described by Strumbelj et. al (2014)
, feature interactions described by
Friedman et. al and tree surrogate models.