FCPS: Fundamental Clustering Problems Suite

Many conventional Clustering Algorithms are provided in this package with consistent input and output, which enables the user to tryout algorithms swiftly. Additionally, 26 statistical approaches for the estimation of the number of clusters as well as the the mirrored density plot (MD-plot) of clusterability are provided. Moreover, the fundamental clustering problems suite (FCPS) offers a variety of clustering challenges any algorithm should handle when facing real world data. Nine of the here presented artificial datasets were named FCPS in Ultsch, A.: "Clustering with SOM: U*C", In Workshop on Self-Organizing Maps, 2005.

Version: 1.1.0
Depends: R (≥ 3.5.0)
Imports: mclust, ggplot2, DataVisualizations
Suggests: kernlab, cclust, vegan, dbscan, kohonen, MCL, ADPclust, cluster, DatabionicSwarm, orclus, subspace, flexclust, ABCanalysis, apcluster, pracma, EMCluster, pdfCluster, parallelDist, plotly, ProjectionBasedClustering, GeneralizedUmatrix, mstknnclust, densityClust, parallel, energy, R.utils, tclust, Spectrum, genie, protoclust, fastcluster, clusterability, signal, reshape2
Published: 2020-03-13
Author: Michael Thrun [aut, cre, cph], Peter Nahrgang [ctr, ctb], Alfred Ultsch [dtc, ctb]
Maintainer: Michael Thrun <m.thrun at gmx.net>
License: GPL-3
NeedsCompilation: no
Citation: FCPS citation info
CRAN checks: FCPS results

Downloads:

Reference manual: FCPS.pdf
Package source: FCPS_1.1.0.tar.gz
Windows binaries: r-devel: FCPS_1.1.0.zip, r-devel-gcc8: FCPS_1.1.0.zip, r-release: FCPS_1.1.0.zip, r-oldrel: FCPS_1.1.0.zip
OS X binaries: r-release: FCPS_1.1.0.tgz, r-oldrel: FCPS_1.1.0.tgz
Old sources: FCPS archive

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