Interpretability of complex machine learning models is a growing concern.
This package helps to understand key factors that drive the
decision made by complicated predictive model (so called black box model).
This is achieved through local approximations that are either based on
additive regression like model or CART like model that allows for
higher interactions. The methodology is based on Tulio Ribeiro, Singh, Guestrin (2016)
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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