xtractvars {klaR} | R Documentation |
Variable clustering based variable selection
Description
Applies variable selection to data based on variable clusterings as resulting from corclust
or CLV
.
Usage
xtractvars(object, data, thres = 0.5)
Arguments
object |
Object of class |
data |
Data where variables are to be selected. Coloumn names must be identical to those used in corclust model. |
thres |
Maximum accepted average within cluster correlation for selection of a variable. |
Details
Of each cluster the first variable is selected as well as all other variables with an average within cluster correlation below thres
.
Value
The data is returned where unselected coloumns are removed.
Author(s)
Gero Szepannek
References
Roever, C. and Szepannek, G. (2005): Application of a genetic algorithm to variable selection in fuzzy clustering. In C. Weihs and W. Gaul (eds), Classification - The Ubiquitous Challenge, 674-681, Springer.
See Also
See also corclust
, cvtree
and CLV
.
Examples
data(B3)
ccres <- corclust(B3)
plot(ccres)
cvtres <- cvtree(ccres, k = 3)
newdata <- xtractvars(cvtres, B3, thres = 0.5)