SOMclustering function

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

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

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

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]).

Returns

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

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.

Author(s)

Michael Thrun

Examples

data('Hepta') out=SOMclustering(Hepta$Data,ClusterNo=7,PlotIt=FALSE)
  • Maintainer: Michael Thrun
  • License: GPL-3
  • Last published: 2023-10-19