nomclust (version 2.6.2)

sm: Simple Matching Coefficient (SM)

Description

The function calculates a dissimilarity matrix based on the SM similarity measure.

Usage

sm(data, var.weights = NULL)

Value

The function returns an object of the class "dist".

Arguments

data

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

var.weights

A numeric vector setting weights to the used variables. One can choose the real numbers from zero to one.

Author

Zdenek Sulc.
Contact:

Details

The simple matching coefficient (Sokal, 1958) represents the simplest way of measuring similarity. It does not impose any weights. By a given variable, it assigns the value 1 in case of match and value 0 otherwise.

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.

Sokal R., Michener C. (1958). A statistical method for evaluating systematic relationships. In: Science bulletin, 38(22), The University of Kansas.

See Also

anderberg, burnaby, eskin, gambaryan, good1, goodall1, good2, goodall2, good3, goodall3, good4, goodall4, iof, lin, lin1, of, smirnov, ve, vm.

Examples

# sample data
data(data20)

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

# dissimilarity matrix calculation with variable weights
weights.sm <- sm(data20, var.weights = c(0.7, 1, 0.9, 0.5, 0))