HI, Saeed,
It worked this time.
Thanks, I appreciated it very much!
On Thu, Apr 29, 2010 at 5:23 PM, Saeed Abu Nimeh wrote:
> in svm.roc <- prediction(attributes(svm.pred)$decision.values, valid)
> valid should be the output variable in the validation set. maybe
> valid[,1] assuming that it
HI, Saeed,
Thanks so much for the help, I run your code and found the following
problem, do you have any comments or suggestions?
> svm.p<-svm(as.factor(out) ~ ., data=train[,c( 2:18, 20:21, 24, 27:32)],
probability=TRUE, method="C-classification",
+ kernel="radial", cost=bestc, gamma=bestg, cros
svm.model <- svm(y~.,data=dataset,probability=TRUE)
svm.pred<-predict(svm.model, test.set, decision.values = TRUE,
probability = TRUE)
library(ROCR)
svm.roc <- prediction(attributes(svm.pred)$decision.values, test.set)
svm.auc <- performance(svm.roc, 'tpr', 'fpr')
plot(svm.auc)
On Thu, Apr
> x <- train[,c( 2:18, 20:21, 24, 27:31)]
> y <- train$out
>
> svm.pr <- svm(x, y, probability = TRUE, method="C-classification",
kernel="radial", cost=bestc, gamma=bestg, cross=10)
>
> pred <- predict(svm.pr, valid[,c( 2:18, 20:21, 24, 27:31)],
decision.values = TRUE, probability = TRUE)
> at
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