MinimalEnergyClustering: Minimal Energy Clustering

In FCPS: Fundamental Clustering Problems Suite

Minimal Energy Clustering

Description

Hierchical Clustering using the minimal energy approach of [Szekely/Rizzo, 2005].

Usage

MinimalEnergyClustering(DataOrDistances, ClusterNo = 0,
DistanceMethod="euclidean", ColorTreshold = 0,Data,...)

Arguments

DataOrDistances	[1:n,1:d] matrix of dataset to be clustered. It consists of n cases of d-dimensional data points. Every case has d attributes, variables or features. Alternatively, symmetric [1:n,1:n] distance matrix
ClusterNo	A number k which defines k different clusters to be build by the algorithm.
DistanceMethod	See parDist, for example 'euclidean','mahalanobis','manhatten' (cityblock),'fJaccard','binary', 'canberra', 'maximum'. Any unambiguous substring can be given.
ColorTreshold	Draws cutline w.r.t. dendogram y-axis (height), height of line as scalar should be given
Data	[1:n,1:d] data matrix in the case that DataOrDistances is missing and partial matching does not work.
...	In case of plotting further argument for plot, see as.dendrogram

Value

List of

Cls	If ClusterNo>0: [1:n] numerical vector with n numbers defining the classification as the main output of the clustering algorithm. It has k unique numbers representing the arbitrary labels of the clustering. Otherwise ClusterNo=0: NULL
Dendrogram	Dendrogram of hierarchical clustering algorithm
Object	Ultrametric tree of hierarchical clustering algorithm

Author(s)

Michael Thrun

References

[Szekely/Rizzo, 2005] Szekely, G. J. and Rizzo, M. L.: Hierarchical Clustering via Joint Between-Within Distances: Extending Ward's Minimum Variance Method, Journal of Classification, 22(2) 151-183.http://dx.doi.org/10.1007/s00357-005-0012-9, 2005.

See Also

HierarchicalClustering

Examples

data('Hepta')
out=MinimalEnergyClustering(Hepta$Data,ClusterNo=7)

FCPS documentation built on Oct. 19, 2023, 5:06 p.m.