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) <doi:10.1145/2939672.2939778>. More details can be found in Staniak, Biecek (2018) <arXiv:1804.01955>.
|Author||Mateusz Staniak [cre, aut], Przemysław Biecek [aut]|
|Maintainer||Mateusz Staniak <[email protected]>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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