| sm {nomclust} | R Documentation |
Simple Matching Coefficient (SM)
Description
The function calculates a dissimilarity matrix based on the SM similarity measure.
Usage
sm(data, var.weights = NULL)
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. |
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.
Value
The function returns an object of the 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.
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,
goodall1,
goodall2,
goodall3,
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))