@pagal_guy wrote:
hello,
As can be seen there is a difference in the two methods used above.
#SVM 1:
X <- train1[,c(15:51)]
svmfit.radial <- train(as.factor(Recommended) ~ ., data = X,method = "svmRadial",trControl = ctrl)
svmfit.radial# SVM 2: library(kernlab) svmfit.lssvmradial <- train(as.factor(Recommended) ~ ., data = X,method = "lssvmRadial",trControl = ctrl) svmfit.lssvmradial
Can someone please guide me on how these two implementations of SVM differ??
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