Construct Explainable Nomogram for a Machine Learning Model R package rmlnomogram version 0.1.2 Construct an explainable nomogram for a machine learning (ML) model to improve availability of an ML prediction model in addition to a computer application, particularly in a situation where a computer, a mobile phone, an internet connection, or the application accessibility are unreliable. This package enables a nomogram creation for any ML prediction models, which is conventionally limited to only a linear/logistic regression model. This nomogram may indicate the explainability value per feature, e.g., the Shapley additive explanation value, for each individual. However, this package only allows a nomogram creation for a model using categorical without or with single numerical predictors. Detailed methodologies and examples are documented in our vignette, available at <https://htmlpreview.github.io/?https://github.com/herdiantrisufriyana/rmlnomogram/blob/master/doc/ml_nomogram_exemplar.html>. Software Depends: R (>= 4.4) Imports: dplyr, purrr, broom, stats, ggplot2, ggpubr, stringr, tidyr, utils Suggests: tidyverse, knitr, caret, randomForest, iml, testthat (>= 3.0.0) Herdiantri Sufriyana <herdi@nycu.edu.tw> Comprehensive R Archive Network (CRAN) Herdiantri Sufriyana [aut, cre] (ORCID: <https://orcid.org/0000-0001-9178-0222>), Emily Chia-Yu Su [aut] (ORCID: <https://orcid.org/0000-0003-4801-5159>) MIT + file LICENSE (https://CRAN.R-project.org/package=rmlnomogram/LICENSE) 2025-01-08 application/tgz https://CRAN.R-project.org/package=rmlnomogram doi:10.32614/CRAN.package.rmlnomogram