FCPS-package |
FCPC Data Sets with Common Clustering Algorithms |
ADPclustering |
(Adaptive) Density Peak Clustering algorithm using Automatic Parameter Selection |
AgglomerativeNestingClustering |
AGNES clustering |
APclustering |
Affinity Propagation clustering |
Atom |
Atom of [Ultsch, 2004]. |
Chainlink |
Chainlink of [Ultsch et al., 1994; Ultsch, 1995]. |
ClusterabilityMDplot |
Clusterability MDplot |
ClusterDistances |
ClusterDistances |
ClusteringAccuracy |
ClusteringAccuracy |
ClusteringAlgorithms |
FCPC Data Sets with Common Clustering Algorithms |
Clusternumbers |
Estimates Number of Clusters using up to 26 Indicators |
DatabionicSwarmClustering |
Databionic Swarm (DBS) Clustering and Visualization |
DBscan |
DBscan |
DBSclusteringAndVisualization |
Databionic Swarm (DBS) Clustering and Visualization |
DensityPeakClustering |
Density Peak Clustering algorithm using the Decision Graph |
DivisiveAnalysisClustering |
Large DivisiveAnalysisClustering Clustering |
EngyTime |
EngyTime of [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. 164-198] |
GenerateFundamentalClusteringProblem |
Generates a Fundamental Clustering Problem based on specific artificial datasets. |
GenieClustering |
Genie Clustering by Gini Index |
GolfBall |
GolfBall of [Ultsch, 2005] |
GraphBasedClustering |
MST-kNN clustering algorithm |
HCLclustering |
On-line Update (Hard Competitive learning) method |
Hepta |
Hepta of [Ultsch, 2003] |
HierarchicalCluster |
Hierarchical Clusterering |
HierarchicalClusterData |
Hierarchical Clusterering |
HierarchicalClusterDists |
HierarchicalClusterDists(pDist) HierarchicalClusterDists(pDist,0,"ward.D",100) Cls=HierarchicalClusterDists(pDist,6,"ward.D") Zeichnet entweder ein Dendrogram oder liefert eine Klassenzuweisung |
HierarchicalClustering |
Hierarchical Clustering |
Hierarchical_DBSCAN |
Hierarchical DBSCAN |
InterClusterDistances |
InterClusterDistances |
kmeansClustering |
K-Means Clustering |
LargeApplicationClustering |
Large Application Clustering |
Leukemia |
Leukemia Distancematrix and classificiation used in [Thrun, 2018] |
Lsun |
Lsun from FCPS |
Lsun3D |
Lsun3D inspired by FCPS |
MarkovClustering |
Markov Clustering |
MinimalEnergyClustering |
Minimal Energy Clustering |
MinimaxLinkageClustering |
Minimax Linkage Hierarchical Clustering |
MinSpanTree |
Zeichnet einen 2 dimensionalen minimal spanning Tree |
ModelBasedClustering |
Model Based Clustering |
MoGclustering |
MoGclustering |
NeuralGasClustering |
Neural gas algorithm for clustering |
OPTICSclustering |
OPTICS Clustering |
PAMClustering |
Partitioning Around Medoids (PAM) |
PAMclustering |
Partitioning Around Medoids (PAM) |
pdfClustering |
Probability Density Distribution Clustering |
QTClustering |
Stochastic QT Clustering |
QTclustering |
Stochastic QT Clustering |
RobustTrimmedClustering |
Robust Trimmed Clustering Clustering |
SharedNearestNeighborClustering |
SNN clustering |
SOMclustering |
self-organizing maps based clustering implemented by [Wherens, Buydens, 2017]. |
SpectralClustering |
Spectral Clustering |
Spectrum |
Fast Adaptive Spectral Clustering [John et al, 2020] |
StatPDEdensity |
Pareto Density Estimation |
SubspaceClustering |
Algorithms for Subspace clustering |
Target |
Target of [Ultsch, 2005]. |
Tetra |
Tetra of [Ultsch, 1993] |
TwoDiamonds |
TwoDiamonds of [Ultsch, 2003a, 2003b] |
WingNut |
WingNut of [Ultsch, 2005] |