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evclust: Evidential Clustering

Various clustering algorithms that produce a credal partition, i.e., a set of Dempster-Shafer mass functions representing the membership of objects to clusters. The mass functions quantify the cluster-membership uncertainty of the objects. The algorithms are: Evidential c-Means, Relational Evidential c-Means, Constrained Evidential c-Means, Evidential Clustering, Constrained Evidential Clustering, Evidential K-nearest-neighbor-based Clustering, Bootstrap Model-Based Evidential Clustering, Belief Peak Evidential Clustering, Neural-Network-based Evidential Clustering.

Version: 2.0.3
Depends: R (≥ 3.6.0)
Imports: FNN, R.utils, limSolve, Matrix, mclust, quadprog, plyr
Suggests: utils, kernlab, MASS
Published: 2023-11-09
DOI: 10.32614/CRAN.package.evclust
Author: Thierry Denoeux
Maintainer: Thierry Denoeux <tdenoeux at utc.fr>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
In views: Cluster
CRAN checks: evclust results

Documentation:

Reference manual: evclust.pdf
Vignettes: evclust_vignette

Downloads:

Package source: evclust_2.0.3.tar.gz
Windows binaries: r-devel: evclust_2.0.3.zip, r-release: evclust_2.0.3.zip, r-oldrel: evclust_2.0.3.zip
macOS binaries: r-release (arm64): evclust_2.0.3.tgz, r-oldrel (arm64): evclust_2.0.3.tgz, r-release (x86_64): evclust_2.0.3.tgz, r-oldrel (x86_64): evclust_2.0.3.tgz
Old sources: evclust archive

Reverse dependencies:

Reverse imports: evreg

Linking:

Please use the canonical form https://CRAN.R-project.org/package=evclust to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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