ClusterDistances: ClusterDistances

In FCPS: Fundamental Clustering Problems Suite

ClusterDistances

Description

Computes intra-cluster distances which are the distance in-between each cluster.

Usage

ClusterDistances(FullDistanceMatrix, Cls,

Names, PlotIt = FALSE)

ClusterIntraDistances(FullDistanceMatrix, Cls,

Names, PlotIt = FALSE)

Arguments

FullDistanceMatrix	[1:n,1:n] symmetric distance matrix
Cls	[1:n] numerical vector of k classes
Names	Optional [1:k] character vector naming k classes
PlotIt	Optional, Plots if TRUE

Details

Cluster distances are given back as a matrix, one column per cluster and the vector of the full distance matrix without the diagonal elements and the upper half of the symmetric matrix. Details and definitons can be found in [Thrun, 2021].

Value

Matrix [1:m,1:(k+1)] of k clusters, each columns consists of the distances in a cluster, filled up with NaN at the end to be of the same length as the vector of the upper triangle of the complete distance matrix.

Author(s)

Michael Thrun

References

[Thrun, 2021] Thrun, M. C.: The Exploitation of Distance Distributions for Clustering, International Journal of Computational Intelligence and Applications, Vol. 20(3), pp. 2150016, DOI: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1142/S1469026821500164")}, 2021.

See Also

MDplot

ClusterInterDistances

Examples

data(Hepta)
Distance=as.matrix(dist(Hepta$Data))

interdists=ClusterDistances(Distance,Hepta$Cls)

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