[R] Can't see what i did wrong..

[Jessica Streicher]

with

pred.pca<-predict(splits[[i]]$pca,trainingData at samples)[,1:nPCs]
dframe<-as.data.frame(cbind(pred.pca,class=isExplosive(trainingData,2)));
results[[i]]$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]]$pca,trainingData at samples)[,1:nPCs]
pred.svm<-kernlab::predict(results[[i]]$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?