Introduction | Methodology | Unsupervised models | Preparing the data | Semi-supervised models | Encoding partial supervision | Fitting the models | Additional details | The $\Gamma$ parameter in possibilistic models | Retrieving intermediate results
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:
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✨
DESCRIPTION |NEWS
card.svg |card.png
fussclust/json (API)
| # 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.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:e013be6b78. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 141 | ||
| source / vignettes | OK | 157 | ||
| linux-release-x86_64 | OK | 124 | ||
| wasm-release | OK | 156 |
Dependencies:RcppRcppArmadillordist
