HI, Saeed, It worked this time.
Thanks, I appreciated it very much! On Thu, Apr 29, 2010 at 5:23 PM, Saeed Abu Nimeh <sabun...@gmail.com> wrote: > in svm.roc <- prediction(attributes(svm.pred)$decision.values, valid) > valid should be the output variable in the validation set. maybe > valid[,1] assuming that it is in the first column. I think this is a > typo in my example :) > > On Thu, Apr 29, 2010 at 5:13 PM, Changbin Du <changb...@gmail.com> wrote: > > > > > > HI, Saeed, > > > > Thanks so much for the help, I run your code and found the following > > problem, do you have any comments or suggestions? > > > >> svm.p<-svm(as.factor(out) ~ ., data=train[,c( 2:18, 20:21, 24, 27:32)], > >> probability=TRUE, method="C-classification", > > + kernel="radial", cost=bestc, gamma=bestg, cross=10) > >> > >> svm.pred<-predict(svm.p, valid, decision.values = TRUE, probability = > >> TRUE) > > > >> library(ROCR) > >> svm.roc <- prediction(attributes(svm.pred)$decision.values, valid) > > Error in prediction(attributes(svm.pred)$decision.values, valid) : > > Number of cross-validation runs must be equal for predictions and > labels. > > > >> length(svm.pred) > > [1] 943 > >> dim(valid) > > [1] 943 32 > > > > > > > > > > > > > > > > > > On Thu, Apr 29, 2010 at 4:49 PM, Saeed Abu Nimeh <sabun...@gmail.com> > wrote: > >> > >> svm.model <- svm(y~.,data=dataset,probability=TRUE) > >> svm.pred<-predict(svm.model, test.set, decision.values = TRUE, > >> probability = TRUE) > >> library(ROCR) > >> svm.roc <- prediction(attributes(svm.pred)$decision.values, test.set) > >> svm.auc <- performance(svm.roc, 'tpr', 'fpr') > >> plot(svm.auc) > >> > >> > >> On Thu, Apr 29, 2010 at 4:17 PM, Changbin Du <changb...@gmail.com> > wrote: > >> >> x <- train[,c( 2:18, 20:21, 24, 27:31)] > >> >> y <- train$out > >> >> > >> >> svm.pr <- svm(x, y, probability = TRUE, method="C-classification", > >> > kernel="radial", cost=bestc, gamma=bestg, cross=10) > >> >> > >> >> pred <- predict(svm.pr, valid[,c( 2:18, 20:21, 24, 27:31)], > >> > decision.values = TRUE, probability = TRUE) > >> >> attr(pred, "decision.values")[1:4,] > >> > 16 23 43 52 > >> > 1.08157648 0.51241842 0.06234319 1.20656580 > >> >> attr(pred, "probabilities")[1:4,] > >> > NULL > >> > > >> > > >> > HI, Dear David and R community, > >> > > >> > I am trying to print out the probabilities and set a threshold for > make > >> > ROC > >> > curve. I dont know why it showed NULL for the probabilities. > >> > > >> > y<-train$out, is consisting of 0 and 1 binary values. > >> > > >> > Can you help me with this? > >> > > >> > Thanks so much! > >> > > >> > > >> > > >> > -- > >> > Sincerely, > >> > Changbin > >> > -- > >> > > >> > [[alternative HTML version deleted]] > >> > > >> > ______________________________________________ > >> > R-help@r-project.org mailing list > >> > https://stat.ethz.ch/mailman/listinfo/r-help > >> > PLEASE do read the posting guide > >> > http://www.R-project.org/posting-guide.html > >> > and provide commented, minimal, self-contained, reproducible code. > >> > > > > > > > > > -- > > Sincerely, > > Changbin > > -- > > > > > > > > > -- Sincerely, Changbin -- [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
