Support Vector Machine 2

set.seed(1)
x <- matrix(rnorm(200 * 2), ncol = 2)
x[1:100,] <- x[1:100,] + 2
x[101:150,] <- x[101:150,] - 2
y <- c(rep(1, 150), rep(2, 50))
dat <- data.frame(x = x, y = as.factor(y))
train <- sample(200, 100)
svmfit1 <- svm(y ~ ., data = dat[train,], kernel = "radial", gamma = 1, cost = 0.01)
svmfit2 <- svm(y ~ ., data = dat[train,], kernel = "radial", gamma = 1, cost = 1)
svmfit3 <- svm(y ~ ., data = dat[train,], kernel = "radial", gamma = 1, cost = 1e5)

Je kunt zo vaak indienen als je wenst. Er wordt enkel rekening gehouden met je laatst ingediende oplossing.