burnaby: Burnaby (BU) Measure

In nomclust: Hierarchical Cluster Analysis of Nominal Data

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: [e-mail]

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))

nomclust documentation built on Aug. 18, 2023, 5:06 p.m.