eskin {nomclust}R Documentation

Eskin (ES) Measure

Description

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

Usage

eskin(data)

Arguments

data

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

Details

The Eskin similarity measure was proposed by Eskin et al. (2002) and examined by Boriah et al., (2008). It is constructed to assign higher weights to mismatches on variables with more categories.

Value

The function returns an object of class "dist".

Author(s)

Zdenek Sulc.
Contact: zdenek.sulc@vse.cz

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.

Eskin E., Arnold A., Prerau M., Portnoy L. and Stolfo S. (2002). A geometric framework for unsupervised anomaly detection. In D. Barbara and S. Jajodia (Eds): Applications of Data Mining in Computer Security, p. 78-100. Norwell: Kluwer Academic Publishers.

See Also

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

Examples

# sample data
data(data20)

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

[Package nomclust version 2.2.1 Index]