Package: IBclust 1.4

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. (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>, and the generalized 'IB' from Strouse and Schwab (2017) <doi:10.1162/NECO_a_00961>.
Authors:
IBclust_1.4.tar.gz
IBclust_1.4.zip(r-4.7)IBclust_1.4.zip(r-4.6)IBclust_1.4.zip(r-4.5)
IBclust_1.4.tgz(r-4.6-x86_64)IBclust_1.4.tgz(r-4.6-arm64)IBclust_1.4.tgz(r-4.5-x86_64)IBclust_1.4.tgz(r-4.5-arm64)
IBclust_1.4.tar.gz(r-4.7-arm64)IBclust_1.4.tar.gz(r-4.7-x86_64)IBclust_1.4.tar.gz(r-4.6-arm64)IBclust_1.4.tar.gz(r-4.6-x86_64)
IBclust_1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
IBclust/json (API)
| # Install 'IBclust' in R: |
| install.packages('IBclust', repos = c('https://amarkos.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/amarkos/ibclust/issues
Last updated from:231def61bd. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 179 | ||
| linux-devel-x86_64 | OK | 171 | ||
| source / vignettes | OK | 203 | ||
| linux-release-arm64 | OK | 166 | ||
| linux-release-x86_64 | OK | 173 | ||
| macos-release-arm64 | OK | 142 | ||
| macos-release-x86_64 | OK | 278 | ||
| macos-oldrel-arm64 | OK | 156 | ||
| macos-oldrel-x86_64 | OK | 202 | ||
| windows-devel | OK | 169 | ||
| windows-release | OK | 173 | ||
| windows-oldrel | OK | 141 | ||
| wasm-release | OK | 116 |
Exports:AIBmixDIBmixfind_elbowGIBmixIBmixinfo_metrics
Dependencies:bootcubaturelatticeMASSMatrixMatrixModelsnpquadprogquantregrbibutilsRcppRcppArmadilloRcppEigenRdpackrjeSparseMsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| IBclust: Information Bottleneck Clustering for Mixed-Type Data | IBclust-package IBclust |
| Methods for aibclust objects | aibclust-methods coef.aibclust fitted.aibclust plot.aibclust print.aibclust print.summary.aibclust summary.aibclust |
| Agglomerative Information Bottleneck Clustering for Mixed-Type Data | AIBmix |
| Convert an aibclust object to hclust or dendrogram | as.dendrogram.aibclust as.hclust.aibclust |
| Deterministic Information Bottleneck Clustering for Mixed-Type Data | DIBmix |
| Detect a knee/elbow in a monotone curve | find_elbow |
| Methods for gibclust objects | coef.gibclust fitted.gibclust gibclust-methods plot.gibclust print.gibclust print.summary.gibclust summary.gibclust |
| Generalised Information Bottleneck Clustering for Mixed-Type Data | GIBmix |
| Information Bottleneck Clustering for Mixed-Type Data | IBmix |
| Extract information-theoretic metrics from an IBclust fit | info_metrics info_metrics.aibclust info_metrics.gibclust |
| Predict cluster assignments for new observations | predict.gibclust |
