Information Bottleneck Methods for Clustering Mixed-Type Data
Overview
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, generalised, sequential, and standard IB clustering algorithms that preserve relevant information while forming interpretable clusters. The Deterministic Information Bottleneck is described in Costa et al. (2026) doi:10.1016/j.patcog.2026.113580. 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, the generalised IB from Strouse and Schwab (2017) doi:10.1162/NECO_a_00961, and the sequential IB from Slonim et al. (2002) doi:10.1145/564376.564401. Diagnostic and plotting functions are provided to summarise, visualise, and predict from the resulting clusterings.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK14 OK2026-04-22
Show 2 earlier changesHide 2 earlier changes
- ERROR13 OK, 1 ERROR2026-04-18
- OK14 OK2026-03-10
Documentation
- Help pages
- 14includes a package overview page
- Examples that run
- 100%8 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 43% with a bibliography file
Downloads
Dependencies
Code & Tests
People & History
Package metadata
- First published
- 2025-07-10
- Total releases
- 5 / 1 yrs
- License
- GPL (>= 3) OSI · relicensed from MIT + file LICENSE in 1.2.1
- Minimum R
- ≥ 3.5.0
- Download size
- 201 KB
Cite
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Run in R for the authors' entry:
citation("IBclust")The package provides a citation file, so citation() returns the authors' own entry.
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