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FCPS  

Fundamental Clustering Problems Suite
View on CRAN: Click here


Download and install FCPS package within the R console
Install from CRAN:
install.packages("FCPS")

Install from Github:
library("remotes")
install_github("cran/FCPS")

Install by package version:
library("remotes")
install_version("FCPS", "1.4.1")



Attach the package and use:
library("FCPS")
Maintained by
Michael Thrun
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-02-11
Latest Update: 2023-10-19
Description:
Over sixty clustering algorithms are provided in this package with consistent input and output, which enables the user to try out algorithms swiftly. Additionally, 26 statistical approaches for the estimation of the number of clusters as well as the mirrored density plot (MD-plot) of clusterability are implemented. The packages is published in Thrun, M.C., Stier Q.: "Fundamental Clustering Algorithms Suite" (2021), SoftwareX, . Moreover, the fundamental clustering problems suite (FCPS) offers a variety of clustering challenges any algorithm should handle when facing real world data, see Thrun, M.C., Ultsch A.: "Clustering Benchmark Datasets Exploiting the Fundamental Clustering Problems" (2020), Data in Brief, .
How to cite:
Michael Thrun (2020). FCPS: Fundamental Clustering Problems Suite. R package version 1.4.1, https://cran.r-project.org/web/packages/FCPS. Accessed 28 Oct. 2026.
Previous versions and publish date:
1.0.0 (2020-02-11 11:50), 1.1.0 (2020-03-13 13:50), 1.2.0 (2020-04-23 18:10), 1.2.2 (2020-06-07 16:30), 1.2.3 (2020-06-26 14:40), 1.2.4 (2020-09-07 12:30), 1.2.6 (2020-12-11 23:10), 1.2.7 (2021-01-15 14:10), 1.3.0 (2021-07-07 19:10), 1.3.1 (2022-05-20 18:40), 1.3.3 (2023-05-30 09:40), 1.3.4 (2023-10-19 15:20), 1.3.5 (2025-10-30 18:30), 1.3.6 (2026-03-26 12:10), 1.4.0 (2026-07-15 16:50), 1.4.1 (2026-08-20 10:12), (2026-10-03 10:20)
Other packages that cited FCPS R package
View FCPS citation profile
Other R packages that FCPS depends, imports, suggests or enhances
Complete documentation for FCPS
Functions, R codes and Examples using the FCPS R package
Some associated functions: ADPclustering . APclustering . AgglomerativeNestingClustering . Atom . AutomaticProjectionBasedClustering . Chainlink . ClusterAccuracy . ClusterApply . ClusterChallenge . ClusterCount . ClusterCreateClassification . ClusterDaviesBouldinIndex . ClusterDendrogram . ClusterDistances . ClusterDunnIndex . ClusterEqualWeighting . ClusterInterDistances . ClusterMCC . ClusterNoEstimation . ClusterNormalize . ClusterPlotMDS . ClusterRedefine . ClusterRename . ClusterRenameDescendingSize . ClusterShannonInfo . ClusterUpsamplingMinority . ClusterabilityMDplot . DBscan . DatabionicSwarmClustering . DensityPeakClustering . DivisiveAnalysisClustering . EngyTime . EntropyOfDataField . EstimateRadiusByDistance . FCPS-package . FannyClustering . GenieClustering . GolfBall . HCLclustering . HDDClustering . Hepta . HierarchicalClusterData . HierarchicalClusterDists . HierarchicalClustering . HierarchicalDBSCAN . LargeApplicationClustering . Leukemia . Lsun3D . MSTclustering . MarkovClustering . MinimalEnergyClustering . MinimaxLinkageClustering . MoGclustering . ModelBasedClustering . ModelBasedVarSelClustering . NetworkClustering . NeuralGasClustering . OPTICSclustering . PAMclustering . PenalizedRegressionBasedClustering . ProjectionPursuitClustering . QTclustering . RobustTrimmedClustering . SOMclustering . SOTAclustering . SharedNearestNeighborClustering . SparseClustering . SpectralClustering . Spectrum . StatPDEdensity . SubspaceClustering . TandemClustering . Target . Tetra . TwoDiamonds . WingNut . kmeansClustering . kmeansDist . pdfClustering . 
Some associated R codes: ADPclustering.R . APclustering.R . AgglomerativeNestingClustering.R . AutomaticProjectionBasedClustering.R . ClusterAccuracy.R . ClusterApply.R . ClusterChallenge.R . ClusterCount.R . ClusterCreateClassification.R . ClusterDaviesBouldinIndex.R . ClusterDendrogram.R . ClusterDistances.R . ClusterDunnIndex.R . ClusterEqualWeighting.R . ClusterInterDistances.R . ClusterMCC.R . ClusterNoEstimation.R . ClusterNormalize.R . ClusterPlotMDS.R . ClusterRedefine.R . ClusterRename.R . ClusterRenameDescendingSize.R . ClusterShannonInfo.R . ClusterUpsamplingMinority.R . ClusterabilityMDplot.R . DBscan.R . DatabionicSwarmClustering.R . DensityPeakClustering.R . DivisiveAnalysisClustering.R . EntropyOfDataField.R . EstimateRadiusByDistance.R . FannyClustering.R . GenieClustering.R . HCLclustering.R . HDDClustering.R . HierarchicalClusterData.R . HierarchicalClusterDists.R . HierarchicalClustering.R . HierarchicalDBSCAN.R . LargeApplicationClustering.R . MSTclustering.R . MarkovClustering.R . MinimalEnergyClustering.R . MinimaxLinkageClustering.R . MoGclustering.R . ModelBasedClustering.R . ModelBasedVarSelClustering.R . NetworkClustering.R . NeuralGasClustering.R . OPTICSclustering.R . PAMclustering.R . PenalizedRegressionBasedClustering.R . ProjectionPursuitClustering.R . QTclustering.R . RobustTrimmedClustering.R . SOMclustering.R . SOTAclustering.R . SharedNearestNeighborClustering.R . SparseClustering.R . SpectralClustering.R . Spectrum.R . SubspaceClustering.R . TandemClustering.R . internalMDSestimate.R . kmeansClustering.R . kmeansDist.R . pdfClustering.R .  Full FCPS package functions and examples
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