midr-package {midr} | R Documentation |
midr: Learning from Black-Box Models by Maximum Interpretation Decomposition
Description
The goal of 'midr' is to provide a model-agnostic method for interpreting and explaining black-box predictive models by creating a globally interpretable surrogate model. The package implements 'Maximum Interpretation Decomposition' (MID), a functional decomposition technique that finds an optimal additive approximation of the original model. This approximation is achieved by minimizing the squared error between the predictions of the black-box model and the surrogate model. The theoretical foundations of MID are described in Iwasawa & Matsumori (2025) [Forthcoming], and the package itself is detailed in Asashiba et al. (2025) doi:10.48550/arXiv.2506.08338.
Author(s)
Maintainer: Ryoichi Asasihba ryoichi.asashiba@gmail.com
Authors:
Hirokazu Iwasawa
Other contributors:
Reiji Kozuma [contributor]
See Also
Useful links:
Report bugs at https://github.com/ryo-asashi/midr/issues