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svmmodel
2013 Jan 15
0
e1071 SVM, cross-validation and overfitting
...x, sd = 0.2)
plot(x, y, col="gray80")
legend("topleft",
c("log(x) + cos(x)", "SVM, untuned", "SVM, tuned"),
bty="n",
col=colors,
pch=20)
lines(x, f(x), col = colors[1]) # overlay noiseless data
# SVM, untuned
svmmodel1 <- svm(x, y)
print(summary(svmmodel1))
y1 <- predict(svmmodel1, x)
lines(x, y1, col = colors[2])
# SVM with tuning
tuning <- tune.svm(x, y, gamma = 2^(-4:4), cost = 2^(-2:2))
svmmodel2 <- tuning$best.model
print(summary(svmmodel2))
y2 <- predict(svmmodel2, x)
lines(x, y2, col = colo...