aplime: Adaptive Piecewise Local Model-Agnostic Explanations
Implements Adaptive Piecewise Local Interpretable
Model-Agnostic Explanations (AP-LIME) and its second-order
interaction extension (AP2-LIME) for interpreting predictions
from machine learning models. The methods replace the
conventional locally weighted linear surrogate in LIME with
Multivariate Adaptive Regression Splines (MARS).
AP-LIME uses additive piecewise-linear hinge functions,
whereas AP2-LIME allows pairwise interactions between
hinge functions. The package generates proximity-weighted
local explanations, estimates feature contributions,
evaluates local surrogate fit, and assesses explanation
stability across repeated runs. Stability is measured
using the Variables Stability Index (VSI) and Coefficients
Stability Index (CSI), including normal-theory and
percentile bootstrap confidence intervals. MARS terms
with the same predictors, hinge directions, and interaction
structure are matched independently of knot locations.
Coefficients within matched groups are summarized by
their arithmetic mean, while the original knot thresholds
remain available for inspection. The MARS-based local explanation
approach is discussed by Somuncuoglu and Purutcuoglu
(2027, ISBN:978-1-041-34431-5),
"Explainable AI Approaches in Biomedical Signals:
A Case Study with Pima Indians Diabetes Dataset",
in "Biomedical Data Science: A Focus on Signaling",
CRC Press.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
earth, stats, utils |
| Suggests: |
testthat (≥ 3.0.0), xgboost |
| Published: |
2026-11-12 |
| DOI: |
10.32614/CRAN.package.aplime (may not be active yet) |
| Author: |
Abdullah Nuri Somuncuoğlu [aut] (affiliation: Department of Biomedical
Engineering, Middle East Technical University),
Vilda Purutçuoğlu [aut, cre] (affiliation: Department of Statistics,
Middle East Technical University) |
| Maintainer: |
Vilda Purutçuoğlu <vpurutcu at metu.edu.tr> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| CRAN checks: |
aplime results |
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