IBclust: Information Bottleneck Methods for Clustering Mixed-Type Data
Implements multiple variants of the Information Bottleneck ('IB') method
for clustering datasets containing mixed-type variables (nominal, ordinal, and
continuous). 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' for Gaussian variables from Chechik et al. (2005) <https://www.jmlr.org/papers/volume6/chechik05a/chechik05a.pdf>.
| Version: |
1.2 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp, stats, utils, np, rje, Rdpack, RcppEigen |
| LinkingTo: |
Rcpp, RcppArmadillo, RcppEigen |
| Published: |
2025-07-10 |
| 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: |
MIT + file LICENSE |
| NeedsCompilation: |
yes |
| Citation: |
IBclust citation info |
| Materials: |
README |
| CRAN checks: |
IBclust results |
Documentation:
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