clustindex {cclust}R Documentation

Cluster Indexes

Description

clres is the result of a clustering algorithm of class such as "cclust". This function is calculating the values of several clustering indexes. The values of the indexes can be independenly used in order to determine the number of clusters existing in a data set.

Usage

 clustindex ( clres, x, index = "all" ) 

Arguments

clres An object of a clustering result
x Data matrix
index The indexes being calculated "calinski", "cindex", "db", "hartigan", "ratkowsky", "scott", "marriot", "ball", "trcovw", "tracew", "friedman", "rubin", "ssi", "likelihood", and "all" for all the indexes.

Details

The description of the indexes is categorized into 3 groups, based on the statistics mainly used to compute them.
The first group is based on the sum of squares within (SSW) and between (SSB) the clusters. These statistics measure the dispersion of the data points in a cluster and between the clusters respectively. These indexes are:

The second group is based on the statistics of T, i.e., the scatter matrix of the data points, and W, which is the sum of the scatter matrices in every group. These indexes are: The third group consists of four algorithms not belonging to the previous ones and not having anything in common.

Value

Returns an vector with the indexes values.

Author(s)

Evgenia Dimitriadou and Andreas Weingessel

References

Andreas Weingessel, Evgenia Dimitriadou and Sara Dolnicar, An Examination Of Indexes For Determining The Number Of Clusters In Binary Data Sets,
http://www.wu-wien.ac.at/am/workpap.html#29
and the references therein.

See Also

cclust, kmeans

Examples

# a 2-dimensional example
x<-rbind(matrix(rnorm(100,sd=0.3),ncol=2),
         matrix(rnorm(100,mean=1,sd=0.3),ncol=2))
cl<-cclust(x,2,20,verbose=TRUE,method="kmeans")
resultindexes <- clustindex(cl,x, index="all")
resultindexes   


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