midr-package {midr}R Documentation

midr: Learning from Black-Box Models by Maximum Interpretation Decomposition

Description

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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:

Other contributors:

See Also

Useful links:


[Package midr version 0.5.0 Index]