https://ryo-asashi.r-universe.devRecent package updates in ryo-asashiR-universehttps://github.com/ryo-asashi.pnghttps://ryo-asashi.r-universe.devMon, 04 May 2026 15:13:58 GMTryoichi.asashiba@gmail.com (Ryoichi Asashiba)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>.https://github.com/r-universe/ryo-asashi/actions/runs/26868689509Mon, 04 May 2026 15:13:58 GMTmidr0.6.1.900successhttps://ryo-asashi.r-universe.devhttps://github.com/ryo-asashi/midrryoichi.asashiba@gmail.com (Ryoichi Asashiba)Provides a 'parsnip' engine for the 'midr' package, enabling users to fit, tune, and evaluate Maximum Interpretation Decomposition (MID) models within the 'tidymodels' framework. Developed through research by the Moonlight Seminar 2025, a study group of actuaries from the Institute of Actuaries of Japan, to enhance practical applications of interpretable modeling. Detailed methodology is available in Asashiba et al. (2025) <doi:10.48550/arXiv.2506.08338>.https://github.com/r-universe/ryo-asashi/actions/runs/26868669127Thu, 02 Apr 2026 21:19:16 GMTmidnight0.2.0successhttps://ryo-asashi.r-universe.devhttps://github.com/ryo-asashi/midnight