doi:10.48550/arXiv.2104.07411>, Dandl et al. (2020) <doi:10.1007/978-3-030-58112-1_31> and Wexler et al. (2019) <doi:10.1109/TVCG.2019.2934619>. Optional extensions allow these methods to be applied to a variety of models and use cases. Once generated, the counterfactuals can be analyzed and visualized by provided functionalities.">

counterfactuals: Counterfactual Explanations (original) (raw)

Modular and unified R6-based interface for counterfactual explanation methods. The following methods are currently implemented: Burghmans et al. (2022) <doi:10.48550/arXiv.2104.07411>, Dandl et al. (2020) <doi:10.1007/978-3-030-58112-1_31> and Wexler et al. (2019) <doi:10.1109/TVCG.2019.2934619>. Optional extensions allow these methods to be applied to a variety of models and use cases. Once generated, the counterfactuals can be analyzed and visualized by provided functionalities.

Version: 0.1.6
Depends: R (≥ 3.5.0)
Imports: R6, checkmate, StatMatch, iml, data.table, paradox, miesmuschel, bbotk
Suggests: gower, randomForest, GGally, trtf, testthat, MASS, R.rsp, cowplot, covr, ggplot2, keras, rchallenge, gamlss.data, partykit, mlt, variables, basefun, rmarkdown, rpart, mlr3, mlr3learners, mlr3pipelines, tidymodels, caret, mlr
Published: 2024-10-17
DOI: 10.32614/CRAN.package.counterfactuals
Author: Susanne Dandl ORCID iD [aut, cre], Andreas Hofheinz [aut], Martin Binder [ctb], Giuseppe Casalicchio [ctb]
Maintainer: Susanne Dandl <dandls.datascience at gmail.com>
BugReports: https://github.com/dandls/counterfactuals/issues
License: LGPL-3
URL: https://github.com/dandls/counterfactuals
NeedsCompilation: no
Citation: counterfactuals citation info
Materials: README NEWS
CRAN checks: counterfactuals results

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