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. Moreover, the fundamental clustering problems suite (FCPS) offers a variety of clustering challenges any algorithm should handle when facing real world data. The datasets were introduced in Ultsch, A.: "Clustering with SOM: U*C", In Workshop on Self-Organizing Maps, 2005.

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: mclust
Suggests: DataVisualizations, 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
Published: 2020-02-11
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


Reference manual: FCPS.pdf
Package source: FCPS_1.0.0.tar.gz
Windows binaries: r-devel: not available, r-devel-gcc8: not available, r-release: not available, r-oldrel: not available
OS X binaries: r-release: FCPS_1.0.0.tgz, r-oldrel: FCPS_1.0.0.tgz


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