# another example using the iris
data(iris)
test <- sample(1:150,20)
kpc <- kpca(~.,data=iris[-test,-5],kernel="rbfdot",
kpar=list(sigma=0.2),features=2)
#print the principal component vectors
pcv(kpc)
#plot the data projection on the components
plot(rotated(kpc),col=as.integer(iris[-test,5]),
xlab="1st Principal Component",ylab="2nd Principal Component")
#embed remaining points
emb <- predict(kpc,iris[test,-5])
points(emb,col=as.integer(iris[test,5]))
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