A general-purpose framework for Interpretable Civic-Accountable and Responsible Machine Learning (ICARM). Works with any clean tabular data and automatically detects whether a task is binary classification, multi-class classification, or regression from the target variable type. Provides a single unified entry point civic_fit() alongside tidy interfaces for global and local model explanations, group-level fairness auditing, probability calibration, multi-model comparison, threshold analysis, and reproducible audit trails. Designed to support the DataCitizen-Pro research agenda at Ludwigsburg University of Education: developing data literacy, statistical reasoning, and democratic judgment formation in civic and political teacher education. References: Biecek (2018) <doi:10.18637/jss.v085.i04>, Kuhn (2008) <doi:10.18637/jss.v028.i05>, Awe (2025) <https://github.com/Olawaleawe/civic.icarm>.
| Version: | 0.3.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | stats, utils, rpart, ggplot2, dplyr, tidyr, tibble, purrr, rlang, jsonlite, digest |
| Suggests: | DALEX, glmnet, mgcv, pROC, nnet, testthat, covr, gridExtra |
| Published: | 2026-06-22 |
| DOI: | 10.32614/CRAN.package.civic.icarm |
| 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: | civic.icarm results |
| Reference manual: | civic.icarm.html , civic.icarm.pdf |
| Package source: | civic.icarm_0.3.0.tar.gz |
| Windows binaries: | r-devel: civic.icarm_0.3.0.zip, r-release: civic.icarm_0.3.0.zip, r-oldrel: civic.icarm_0.3.0.zip |
| macOS binaries: | r-release (arm64): civic.icarm_0.3.0.tgz, r-oldrel (arm64): civic.icarm_0.3.0.tgz, r-release (x86_64): civic.icarm_0.3.0.tgz, r-oldrel (x86_64): civic.icarm_0.3.0.tgz |
| Old sources: | civic.icarm archive |
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