SOMclustering: self-organizing maps based clustering implemented by...

In FCPS: Fundamental Clustering Problems Suite

self-organizing maps based clustering implemented by [Wherens, Buydens, 2017].

Description

Either the variant k-batch or k-online is possible in which every unit can be seen approximately as an cluster.

Usage

SOMclustering(Data,LC=c(1,2),ClusterNo=NULL,

Mode="online",PlotIt=FALSE,rlen=100,alpha = c(0.05, 0.01),...)

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.
LC	Lines and Columns of a very small SOM, usually every unit is a cluster, will be ignored if ClusterNo is not NULL.
ClusterNo	Optional, A number k which defines k different clusters to be built by the algorithm. LC will then be set accordingly.
Mode	Either "batch" or "online"
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
rlen	Please see supersom
alpha	Please see supersom
...	Further arguments to be set for the clustering algorithm in somgrid, if not set, default arguments are used.

Details

This clustering algorithm is based on very small maps and, hence, not emergent (c.f. [Thrun, 2018, p.37]). A 3x3 map means 9 units leading to 9 clusters.

Batch is a deterministic clustering approach whereas online is a stochastic clustering approach and research indicates that online should be preferred (c.f. [Thrun, 2018, p.37]).

Value

List of

Cls	[1:n] numerical vector defining the classification as the main output of the clustering algorithm
Object	Object defined by clustering algorithm as the other output of this algorithm

Author(s)

Michael Thrun

References

[Wherens, Buydens, 2017] R. Wehrens and L.M.C. Buydens, J. Stat. Softw. 21 (5), 2007; R. Wehrens and J. Kruisselbrink, submitted, 2017.

[Thrun, 2018] Thrun, M.C., Projection Based Clustering through Self-Organization and Swarm Intelligence. 2018, Heidelberg: Springer.

Examples

data('Hepta')
out=SOMclustering(Hepta$Data,ClusterNo=7,PlotIt=FALSE)

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