Fundamental Clustering Problems Suite

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Documentation for package ‘FCPS’ version 1.3.4

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FCPS-package Fundamental Clustering Problems Suite
ADPclustering (Adaptive) Density Peak Clustering algorithm using automatic parameter selection
AgglomerativeNestingClustering AGNES clustering
APclustering Affinity Propagation Clustering
Atom Atom introduced in [Ultsch, 2004].
AutomaticProjectionBasedClustering Automatic Projection-Based Clustering
Chainlink Chainlink introduced in [Ultsch et al., 1994; Ultsch, 1995].
ClusterabilityMDplot Clusterability MDplot
ClusterAccuracy ClusterAccuracy
ClusterApply Applies a function over grouped data
ClusterARI Adjusted Rand index
ClusterChallenge Generates a Fundamental Clustering Challenge based on specific artificial datasets.
ClusterCount ClusterCount
ClusterCreateClassification Create Classification for Cluster.. functions
ClusterDaviesBouldinIndex Davies Bouldin Index
ClusterDendrogram Cluster Dendrogram
ClusterDistances ClusterDistances
ClusterDunnIndex Dunn Index
ClusterEqualWeighting ClusterEqualWeighting
ClusteringAlgorithms Fundamental Clustering Problems Suite
ClusterInterDistances Computes Inter-Cluster Distances
ClusterIntraDistances ClusterDistances
ClusterMCC Matthews Correlation Coefficient (MCC)
ClusterNoEstimation Estimates Number of Clusters using up to 26 Indicators
ClusterNormalize Cluster Normalize
ClusterPlotMDS Plot Clustering using Dimensionality Reduction by MDS
ClusterRedefine Redfines Clustering
ClusterRename Renames Clustering
ClusterRenameDescendingSize Cluster Rename Descending Size
ClusterShannonInfo Shannon Information
ClusterUpsamplingMinority Cluster Up Sampling using SMOTE for minority cluster
CrossEntropyClustering Cross-Entropy Clustering
DatabionicSwarmClustering Databionic Swarm (DBS) Clustering and Visualization
DBSclusteringAndVisualization Databionic Swarm (DBS) Clustering and Visualization
DensityPeakClustering Density Peak Clustering algorithm using the Decision Graph
DivisiveAnalysisClustering Large DivisiveAnalysisClustering Clustering
EngyTime EngyTime introduced in [Baggenstoss, 2002].
EntropyOfDataField Entropy Of a Data Field [Wang et al., 2011].
EstimateRadiusByDistance Estimate Radius By Distance
FannyClustering Fuzzy Analysis Clustering [Rousseeuw/Kaufman, 1990, p. 253-279]
GapStatistic Gap Statistic
GenieClustering Genie Clustering by Gini Index
GolfBall GolfBall introduced in [Ultsch, 2005]
HCLclustering On-line Update (Hard Competitive learning) method
HDDClustering HDD clustering is a model-based clustering method of [Bouveyron et al., 2007].
Hepta Hepta introduced in [Ultsch, 2003]
HierarchicalCluster Internal function of Hierarchical Clusterering of Data
HierarchicalClusterData Internal function of Hierarchical Clusterering of Data
HierarchicalClusterDists Internal Function of Hierarchical Clustering with Distances
HierarchicalClustering Hierarchical Clustering
HierarchicalDBSCAN Hierarchical DBSCAN
Hierarchical_DBSCAN Hierarchical DBSCAN
Hierarchical_DBscan Hierarchical DBSCAN
InterClusterDistances Computes Inter-Cluster Distances
IntraClusterDistances ClusterDistances
kmeansClustering K-Means Clustering
kmeansDist k-means Clustering using a distance matrix
LargeApplicationClustering Large Application Clustering
Leukemia Leukemia distance matrix and classificiation used in [Thrun, 2018]
Lsun3D Lsun3D inspired by FCPS introduced in [Thrun, 2018]
MarkovClustering Markov Clustering
MeanShiftClustering Mean Shift Clustering
MinimalEnergyClustering Minimal Energy Clustering
MinimaxLinkageClustering Minimax Linkage Hierarchical Clustering
ModelBasedClustering Model Based Clustering
ModelBasedVarSelClustering Model Based Clustering with Variable Selection
MoGclustering Mixture of Gaussians Clustering using EM
MSTclustering MST-kNN clustering algorithm [Inostroza-Ponta, 2008].
NetworkClustering Network Clustering
NeuralGasClustering Neural gas algorithm for clustering
OPTICSclustering OPTICS Clustering
PAMClustering Partitioning Around Medoids (PAM)
PAMclustering Partitioning Around Medoids (PAM)
pdfClustering Probability Density Distribution Clustering
PenalizedRegressionBasedClustering Penalized Regression-Based Clustering of [Wu et al., 2016].
ProjectionPursuitClustering Cluster Identification using Projection Pursuit as described in [Hofmeyr/Pavlidis, 2019].
QTClustering Stochastic QT Clustering
QTclustering Stochastic QT Clustering
RobustTrimmedClustering Robust Trimmed Clustering
SharedNearestNeighborClustering SNN clustering
SOMclustering self-organizing maps based clustering implemented by [Wherens, Buydens, 2017].
SOTAclustering SOTA Clustering
sotaClustering SOTA Clustering
SparseClustering Sparse Clustering
SpectralClustering Spectral Clustering
Spectrum Fast Adaptive Spectral Clustering [John et al, 2020]
StatPDEdensity Pareto Density Estimation
SubspaceClustering Algorithms for Subspace clustering
TandemClustering Tandem Clustering
Target Target introduced in [Ultsch, 2005].
Tetra Tetra introduced in [Ultsch, 1993]
TwoDiamonds TwoDiamonds introduced in [Ultsch, 2003a, 2003b]
WingNut WingNut introduced in [Ultsch, 2005]