| burnaby {nomclust} | R Documentation |
Burnaby (BU) Measure
Description
The function calculates a dissimilarity matrix based on the BU similarity measure.
Usage
burnaby(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 Burnaby similarity measure was presented in (Burnaby, 1970). The measure assigns low similarity to mismatches on rare values and high similarity to mismatches on frequent values, see (Borian et al., 2008).
Value
The function returns an object of the class "dist".
Author(s)
Zdenek Sulc.
Contact: zdenek.sulc@vse.cz
References
Burnaby T. (1970). On a method for character weighting a similarity coefficient, employing the concept of information.
Mathematical Geology, 2(1), 25-38.
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.
See Also
anderberg,
eskin,
gambaryan,
goodall1,
goodall2,
goodall3,
goodall4,
iof,
lin,
lin1,
of,
sm,
smirnov,
ve,
vm.
Examples
# sample data
data(data20)
# dissimilarity matrix calculation
prox.burnaby <- burnaby(data20)
# dissimilarity matrix calculation with variable weights
weights.burnaby <- burnaby(data20, var.weights = c(0.7, 1, 0.9, 0.5, 0))