nomclust (version 2.1.6)

ve: Variable Entropy (VE) Measure

Description

A function for calculation of a proximity (dissimilarity) matrix based on the VE similarity measure.

Usage

ve(data)

Arguments

data

A data.frame or a matrix with cases in rows and variables in colums.

Value

The function returns a dissimilarity matrix of the size n x n, where n is the number of objects in the original dataset in the argument data.

Details

The Variable Entropy similarity measure was introduced in (Sulc and Rezankova, 2019). It treats the similarity between two categories based on the within-cluster variability expressed by the normalized entropy. The measure assigns higher weights to rare categories.

References

Boriah S., Chandola V., Kumar V. (2008). Similarity measures for categorical data: A comparative evaluation. In: Proceedings of the 8th SIAM International Conference on Data Mining, SIAM, p. 243-254.

Sulc Z. and Rezankova H. (2019). Comparison of Similarity Measures for Categorical Data in Hierarchical Clustering. Journal of Classification. 2019, 35(1), p. 58-72. DOI: 10.1007/s00357-019-09317-5.

See Also

eskin, good1, good2, good3, good4, iof, lin, lin1, morlini, of, sm, vm.

Examples

# NOT RUN {
# sample data
data(data20)

# dissimilarity matrix calculation
prox.ve <- ve(data20)

# }