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CLIQUE: Conditional Local Importance by Quantile Expectations
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 |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=CLIQUE
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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