ClusterRedefine function

Redfines Clustering

Redfines Clustering

Redfines some or all Clusters of Clustering such that the names of the numerical vectors are defined by

ClusterRedefine(Cls, NewLabels,OldLabels)

Arguments

  • Cls: 1:n numerical vector of numbers defining the classification as the main output of the clustering algorithm for the n cases of data. It has k unique numbers representing the arbitrary labels of the clustering.
  • NewLabels: [1:p], p<=k labels (identifiers) of clusters to be changed with
  • OldLabels: Optional, [1:p], p<=k labels(identifiers) of clusters to be changed, default [1:k] unique cluster Ids of Cls

Details

The same ordering of NewLabels and OldLabels is assumend, i.e., the mapping is defined by OldLabels[i] -> NewLabels[i] with i in [1:p]. NewLabels can also be a vector for strings, for example for plotting.

Returns

Cls[1:n] numerical vector named after the row names of data

Author(s)

Michael Thrun

Examples

data('Lsun3D') Cls=Lsun3D$Cls Data=Lsun3D$Data# #prior ClsNew=unique(Cls)+10 #Redfined Clustering NewCls=ClusterRedefine(Cls,ClsNew) table(Cls,NewCls) #require(DataVisualizations) n=length(unique(Cls)) NewCls=ClusterRedefine(Cls,LETTERS[1:n]) #DataVisualizations package required if(requireNamespace("DataVisualizations")) DataVisualizations::Classplot(Data[,1],Data[,2], Cls,Names=NewCls,Plotter="ggplot",Size =1.5)
  • Maintainer: Michael Thrun
  • License: GPL-3
  • Last published: 2023-10-19

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