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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