fmeffects: Model-Agnostic Interpretations with Forward Marginal Effects
Create local, regional, and global explanations for any machine learning model with forward marginal effects. You provide a model and data, and 'fmeffects' computes feature effects. The package is based on the theory in: C. A. Scholbeck, G. Casalicchio, C. Molnar, B. Bischl, and C. Heumann (2022) <doi:10.48550/arXiv.2201.08837>.
| Version: | 
0.1.4 | 
| Depends: | 
R (≥ 3.5.0) | 
| Imports: | 
checkmate, cli, data.table, partykit, ggparty, ggplot2, cowplot, R6, testthat | 
| Suggests: | 
caret, furrr, future, hexbin, knitr, mlr3verse, parallelly, ranger, rmarkdown, rpart, tidymodels | 
| Published: | 
2024-11-05 | 
| DOI: | 
10.32614/CRAN.package.fmeffects | 
| Author: | 
Holger Löwe [cre, aut],
  Christian Scholbeck [aut],
  Christian Heumann [rev],
  Bernd Bischl [rev],
  Giuseppe Casalicchio [rev] | 
| Maintainer: | 
Holger Löwe  <hbj.loewe at gmail.com> | 
| BugReports: | 
https://github.com/holgstr/fmeffects/issues | 
| License: | 
LGPL-3 | 
| URL: | 
https://holgstr.github.io/fmeffects/,
https://github.com/holgstr/fmeffects | 
| NeedsCompilation: | 
no | 
| Materials: | 
README, NEWS  | 
| CRAN checks: | 
fmeffects results | 
Documentation:
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