R/ipmrfnew.R

In IPMRF: Intervention in Prediction Measure (IPM) for Random Forests

ipmrfnew <-
function(marbolr,da,ntree){
#marbolr: randomforest obtained by Randomforest library
#da: data frame with the predictors only, not responses
#ntree: number of trees in the random forest


da=as.data.frame(da)

#percentage of use per tree (if 2 times of a total of 2 splits is more than 2 times of a total of three)
dime=dim(da)
if(is.null(dime)){pup=matrix(0,nrow=1,ncol=length(da))
da=t(as.matrix(da))
dime=dim(da)
}else{
pup=matrix(0,nrow=dime[1],ncol=dime[2])} 



#totob=ntree
ob=dim(da)[1]

totob=rep(ntree,ob)


for (i in 1:ntree){
ar=getTree(marbolr,k=i) #sin label

#ob=dim(da)[1]

#which variables used in prediction
for(j in 1:ob){
da1=da[j,]
wv=prevtree(ar,da1)
if (is.null(wv)){totob[j]=totob[j]-1}
else{

pupi=table(wv)/length(wv)
dond= unique(sort(wv))

pup[j,dond]=pup[j,dond]+ as.numeric(pupi)
}
}
}

#pupf=pup/totob


pupf=pup
for(h in 1:dime[1]){
pupf[h,]=pup[h,]/totob[h]}


dimnames(pupf)=dimnames(da)

return(pupf)
}