nomclust (version 2.1.6)

lin: Lin (LIN) Measure

Description

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

Usage

lin(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 Lin measure was introduced by Lin (1998) and presented in (Boriah et al., 2008). The measure assigns higher weights to more frequent categories in case of matches and lower weights to less frequent categories in case of mismatches.

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.

Lin D. (1998). An information-theoretic definition of similarity. In: ICML '98: Proceedings of the 15th International Conference on Machine Learning. San Francisco, p. 296-304.

See Also

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

Examples

# NOT RUN {
# sample data
data(data20)

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

# }