The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
A general-purpose framework for Interpretable Contextual-Accountable and Responsible Machine Learning (ICARM) that works with any clean tabular data across any application domain including healthcare, finance, social science, business, and education. Automatically detects whether a prediction task is binary classification, multi-class classification, or regression from the target variable type. Provides a unified entry point icarm_fit() supporting both interpretable learners (Classification and Regression Trees (CART), logistic regression, linear regression, Generalized Additive Models (GAM)) and extended learners (random forest, 'XGBoost', Support Vector Machines (SVM)) with consistent interfaces for global and local model explanation, group-level fairness auditing across protected attributes, probability calibration, threshold analysis, multi-model comparison, reproducible JavaScript Object Notation (JSON) audit trails, and accountability scorecards. The contextual accountability framing emphasises that algorithmic fairness and interpretability requirements depend on the deployment domain and must be evaluated accordingly. Extends the 'civic.icarm' framework (Awe 2025) <https://cran.r-project.org/package=civic.icarm> to general-purpose applications beyond civic and political education.
| Version: | 0.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | stats, utils, rpart, ggplot2, dplyr, tidyr, tibble, purrr, rlang, jsonlite, digest |
| Suggests: | randomForest, xgboost, e1071, mgcv, glmnet, nnet, DALEX, pROC, vip, testthat, covr |
| Published: | 2026-06-30 |
| DOI: | 10.32614/CRAN.package.icarm (may not be active yet) |
| Author: | Olushina Olawale Awe [aut, cre], Ludwigsburg University of Education [fnd] |
| Maintainer: | Olushina Olawale Awe <olawaleawe at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Language: | en-GB |
| Materials: | README |
| CRAN checks: | icarm results |
| Reference manual: | icarm.html , icarm.pdf |
| Package source: | icarm_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): icarm_0.1.0.tgz, r-oldrel (arm64): icarm_0.1.0.tgz, r-release (x86_64): not available, r-oldrel (x86_64): not available |
Please use the canonical form https://CRAN.R-project.org/package=icarm to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.