[R] stepwise variable selection method wanted
Alexander.Herr at csiro.au
Alexander.Herr at csiro.au
Thu Jul 30 09:54:47 CEST 2009
Hi List,
I am looking for a variable selection procedure with a forward-backward selection method.
Firstly, it is meant to work with the cophenetic
correlation coefficient (CPCC) and intended to find the variable combination with the
highest cophenetic correlation. Secondly, it is aimed at Gower metric with
wards method (though this could be easily extended) aimed at categorical data.
What I have so far is a function for backward selection that returns the variables
deleted and associated CPCC.
My current approach is cumbersome and very slow when working with large data sets (mostly
because of the proximity matrix calculation). There are also problems with using only
backward selection, so a way of combining forward-backward would be much better. I was hoping that someone has a better /faster selection procedure that can be adapted to using the CPCC.
Below my backward selection function and example.
Thanks and cheers
Herry
################################################
require(cluster)
cophenCbw<-function(dta){
# cophenetic variable selection backward
if(!is.data.frame(dta)) {print("x must be a dataframe with variables as columns, cases as rows")}
else if(ncol(dta) <3) {pring("input dataframe must have at least 3 columns")}
else {
#currently function only performs cophenC on gower with ward, but this can be adjusted easily to other metrics/methods
require(cluster)
require(ade4)
dta->dta.sic
lhs<-dta
for(j in 1:ncol(dta)){
print(paste("round", j))
as.data.frame(matrix(ncol=4, nrow=0))->testm
for(i in 0:ncol(lhs)) {
if(i == 0){
daisy(lhs, metric="gower")->d.all
agnes(lingoes(d.all),method="ward")->agnes.d.all
cophenetic(agnes.d.all)->d1
cor(d1,d.all)->cc
testm<-data.frame(varID=0,cophenC=round(cc,3),varsdel=NA,round=0)
}
else {
daisy(lhs[,-i], metric="gower")->d.all
agnes(lingoes(d.all),method="ward")->agnes.d.all
cophenetic(agnes.d.all)->d1
cor(d1,d.all)->cc
testm<-rbind(testm,data.frame(varID=i,cophenC=round(cc,3),varsdel=colnames(dta)[i],round=j))
#print(paste("var", i, "out of",ncol(lhs),"nrows", nrow(lhs),"rowsInTestm:",nrow(testm)))
}
}
if(j == 1) {
testm[testm[,2] == min(testm[,2]),][1,]->varsdel #use only the first if there are several
vars2del<-varsdel[j,3]
lhs<-dta[,-which(colnames(dta) %in% vars2del)]
print(paste("var2delete",varsdel[j,1],varsdel[j,3],"cophenC=",varsdel[j,2],"rowsInTestm:",nrow(testm)))
} # put exclusion variable into record
else {
rbind(varsdel,testm[testm[,2] == min(testm[,2]),])->varsdel
vars2del<-rbind(vars2del,varsdel[j,3])
lhs<-dta[,-which(colnames(dta) %in% vars2del)]
print(paste("var2delete",varsdel[j,1],varsdel[j,3],"cophenC=",varsdel[j,2],"rowsInTestm:",nrow(testm)))
}
if(is.na(varsdel[j,3])) break
}
}
return(varsdel)
}
cophenCbw(plantTraits)
########################################################
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