IBclust: Information Bottleneck Methods for Clustering Mixed-Type Data
Implements multiple variants of the Information Bottleneck ('IB') method
for clustering datasets containing continuous, categorical (nominal/ordinal) and mixed-type variables.
The package provides deterministic, agglomerative, generalized,
and standard 'IB' clustering algorithms that preserve relevant information while
forming interpretable clusters. The Deterministic Information Bottleneck is described in
Costa et al. (2024) <doi:10.48550/arXiv.2407.03389>. The standard 'IB' method
originates from Tishby et al. (2000) <doi:10.48550/arXiv.physics/0004057>,
the agglomerative variant from Slonim and Tishby (1999) <https://papers.nips.cc/paper/1651-agglomerative-information-bottleneck>,
and the generalized 'IB' from Strouse and Schwab (2017) <doi:10.1162/NECO_a_00961>.
| Version: |
1.2.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp, stats, utils, np, rje, Rdpack, RcppEigen |
| LinkingTo: |
Rcpp, RcppArmadillo, RcppEigen |
| Suggests: |
mclust |
| Published: |
2025-09-19 |
| DOI: |
10.32614/CRAN.package.IBclust |
| Author: |
Efthymios Costa [aut],
Ioanna Papatsouma [aut],
Angelos Markos [aut, cre] |
| Maintainer: |
Angelos Markos <amarkos at gmail.com> |
| License: |
GPL (≥ 3) |
| NeedsCompilation: |
yes |
| Citation: |
IBclust citation info |
| Materials: |
README |
| CRAN checks: |
IBclust results |
Documentation:
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