Provides methods for interpretable machine learning with an
emphasis on local feature importance estimation. The package implements the
CLIQUE framework for computing observation-level importance values.
Additional tools are included for visualizing multi-class partial dependence
relationships across predictors and response classes.
| Version: |
1.0.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
caret, dplyr, fastDummies, future, future.apply, stats, tidyr, ggplot2, ggh4x, randomForest, rlang, pdp |
| Suggests: |
testthat (≥ 3.0.0), datasets |
| Published: |
2026-09-09 |
| DOI: |
10.32614/CRAN.package.CLIQUE (may not be active yet) |
| Author: |
Kelvyn Bladen 
[aut, cre],
Adele Cutler [aut],
D. Richard Cutler [aut],
Kevin R. Moon [aut] |
| Maintainer: |
Kelvyn Bladen <kelvyn.bladen at usu.edu> |
| License: |
GPL-3 |
| URL: |
https://github.com/KelvynBladen/CLIQUE |
| NeedsCompilation: |
no |
| Citation: |
CLIQUE citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
CLIQUE results |