Package: fussclust 0.1.0

Kamil Kmita

fussclust: Fuzzy Unsupervised and Semi-Supervised Clustering

Methods for distance-based fuzzy unsupervised and semi-supervised clustering, including fuzzy and possibilistic models based on alternating optimization (AO) algorithm. The package introduces a vectorized estimation framework for prototype-based fuzzy clustering algorithms, enabling modular algorithm design and extensibility. It also supports storage and retrieval of intermediate AO optimization results for downstream analysis and processing. For more details see Kmita et al. (2024) <doi:10.1109/TFUZZ.2024.3370768>.

Authors:Kamil Kmita [aut, cre, cph]

fussclust_0.1.0.tar.gz
fussclust_0.1.0.tar.gz(r-4.7-any)fussclust_0.1.0.tar.gz(r-4.6-any)
fussclust_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
fussclust/json (API)
NEWS

# Install 'fussclust' in R:
install.packages('fussclust', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • superFstruct_underimpact - Binary supervision structure to reconstruct the issue of underimpact of partial supervision.
  • U_underimpact - Initialization matrix to analyze underimpact in iris data.

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.70 score 4 exports 3 dependencies

Last updated from:e013be6b78. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK116
source / vignettesOK196
linux-release-x86_64OK114
wasm-releaseOK97

Exports:FCMPCMSSFCMSSPCM

Dependencies:RcppRcppArmadillordist

fuzzy-clustering

Rendered fromfuzzy-clustering.Rmdusingknitr::rmarkdownon Jun 02 2026.

Last update: 2026-06-02
Started: 2026-06-02