midr
0.6.1Learning from Black-Box Models by Maximum Interpretation Decomposition
Overview
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.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-2214 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1813 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 94%
- Return-value docs
- 100%
- References docs
- 2%
Downloads
Repository
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5 development-tooling and community-health practices detected across 4 families in the upstream repository
Checks run against github.com/ryo-asashi/midr on 2026-08-09.
Dependencies
Code & Tests
People & History
6 releases. Pick two to compare their code metrics. R releases are shown for context.
Package metadata
- First published
- 2025-06-23
- Total releases
- 6 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 322 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
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