Proximities among individuals using nominal variables.
Proximities among individuals using nominal variables.
CategoricalProximities(Data, SUP = NULL, coefficient = "GOW", transformation = 3, ...)
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 |
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.
A list of Values
Jose Luis Vicente Villardon
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.
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]]))
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.