Package: icarm
Title: Interpretable Contextual-Accountable and Responsible Machine
        Learning
Version: 0.1.0
Authors@R: c(person("Olushina Olawale", "Awe", email = "olawaleawe@gmail.com", role = c("aut", "cre")), person("Ludwigsburg University of Education", role = "fnd"))
Description: 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
        (CART, logistic regression, linear regression, GAM) and
        extended learners (random forest, XGBoost, 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 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.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
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
Config/testthat/edition: 3
LazyData: true
RoxygenNote: 7.3.3
Config/pak/sysreqs: libicu-dev
Repository: https://olawaleawe.r-universe.dev
Date/Publication: 2026-06-18 16:42:38 UTC
RemoteUrl: https://github.com/olawaleawe/icarm
RemoteRef: HEAD
RemoteSha: 67f26ebf7a01663ff7b3620c9e76c4ac96738f9c
NeedsCompilation: no
Packaged: 2026-07-01 11:08:36 UTC; root
Author: Olushina Olawale Awe [aut, cre],
  Ludwigsburg University of Education [fnd]
Maintainer: Olushina Olawale Awe <olawaleawe@gmail.com>