iml

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) doi:10.1080/10618600.2014.907095, local models (variant of 'lime') described by Ribeiro et. al (2016) , the Shapley Value described by Strumbelj et. al (2014) doi:10.1007/s10115-013-0679-x, feature interactions described by Friedman et. al doi:10.1214/07-AOAS148 and tree surrogate models.