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:
Downloads:
Reverse dependencies:
Linking:
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