SOTAclustering: SOTA Clustering

In FCPS: Fundamental Clustering Problems Suite

SOTA Clustering

Description

Self-organizing Tree Algorithm (SOTA) introduced by [Herrero et al., 2001].

Usage

SOTAclustering(Data, ClusterNo,PlotIt=FALSE,UnrestGrowth,...)

Arguments

Data	[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.
ClusterNo	A number k which defines k different clusters to be built by the algorithm.
PlotIt	Default: FALSE, if TRUE plots the first three dimensions of the dataset with colored three-dimensional data points defined by the clustering stored in Cls
UnrestGrowth	TRUE: forces the ClusterNo option to uphold. FALSE: enables the algorithm to find its own number of clusters, in this cases ClusterNo should contain a high number because it is internally set as the number of iterations which is either reached or the max diversity criteria is satisfied priorly.
...	Further arguments to be set for the clustering algorithm, if not set, default arguments are used.

Value

List of

Cls	[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.
sotaObject	Object defined by clustering algorithm as the other output of this algorithm

Note

*Luis Winckelman intergrated several function from clValid because it's ORPHANED.

Author(s)

Luis Winckelmann*, Vasyl Pihur, Guy Brock, Susmita Datta, Somnath Datta

References

[Herrero et al., 2001] Herrero, J., Valencia, A., & Dopazo, J.: A hierarchical unsupervised growing neural network for clustering gene expression patterns, Bioinformatics, Vol. 17(2), pp. 126-136. 2001.

Examples

#Does Work
data('Hepta')
out=SOTAclustering(Hepta$Data,ClusterNo=7)
table(Hepta$Cls,out$Cls)


#Does not work well
data('Lsun3D')
out=SOTAclustering(Lsun3D$Data,ClusterNo=100,PlotIt=FALSE,UnrestGrowth=FALSE)

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