Its not scaling.. so.. I guess i'll stay severely frustrated, and yes i know this is probably not enough information for anyone to help. Still, talking helps ;)
On 15.11.2012, at 15:15, Jessica Streicher wrote: > with > > pred.pca<-predict(splits[[i]]$pca,trainingData@samples)[,1:nPCs] > dframe<-as.data.frame(cbind(pred.pca,class=isExplosive(trainingData,2))); > results[[i]]$classifier<-ksvm(class~.,data=dframe,scaled=T,kernel="polydot",type="C-svc", > > C=C,kpar=list(degree=degree,scale=scale,offset=offset),prob.model=T) > > and a degree of 5 i get an error of 0 reported by the ksvm object. But when > doing > > pred.pca<-predict(splits[[i]]$pca,trainingData@samples)[,1:nPCs] > pred.svm<-kernlab::predict(results[[i]]$classifier,pred.pca,type="probabilities"); > results[[i]]$trainResults$predicted<-pred.svm[,2] > > the results vary widely from the class vector. Nearly all predictions are > somewhat around 0.29. Its just strange. And i have no idea where things go > wrong. They're in the same loop with i, so its probably not an indexing issue. > > Maybe kernlabs predict doesn't scale the data or something? > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
