CategoricalProximities function

Proximities among individuals using nominal variables.

CategoricalProximities(Data, SUP = NULL, coefficient = "GOW", transformation = 3, ...)

Arguments

• Data: A data frame containing categorical (nominal) variables
• SUP: Supplementary data (Used to project supplementary individuals onto the PCoA configuration, for example)
• coefficient: Similarity coefficient to use (see details)
• transformation: Transformation of the similarity into a distance
• ...: Extra parameters

Details

The function calculates similarities and dissimilarities among a set ob ogjects characterized by a set of nominal variables. The function uses similarities and converts into dissimilarities using a variety of transformations controled by the user.

Returns

A list of Values

References

dos Santos, T. R., & Zarate, L. E. (2015). Categorical data clustering: What similarity measure to recommend?. Expert Systems with Applications, 42(3), 1247-1260.

Boriah, S., Chandola, V., & Kumar, V. (2008). Similarity measures for categorical data: A comparative evaluation. red, 30(2), 3.

Author(s)

Jose Luis Vicente Villardon

Examples

data(Doctors)
Dis=CategoricalProximities(Doctors, SUP=NULL, coefficient="GOW" , transformation=3)
pco=PrincipalCoordinates(Dis)
plot(pco, RowCex=0.7, RowColors=as.integer(Doctors[[1]]), RowLabels=as.character(Doctors[[1]]))