If we use the ROCR package to find the accuracy of a classifier pred <- prediction(svm.pred, testset[,2]) perf.acc <- performance(pred,"acc")
Do we find the maximum accuracy as follows (is there a simplier way?): > max(perf....@x.values[[1]]) Then to find the cutoff point that maximizes the accuracy do we do the following (is there a simpler way): > cutoff.list <- unlist(perf....@x.values[[1]]) > cutoff.list[which.max(perf....@y.values[[1]])] If the above is correct how is it possible to find the average false positive and negative rates from the following perf.fpr <- performance(pred, "fpr") perf.fnr <- performance(pred, "fnr") The dataset that consists of two columns; score and a binary response, similar to this: 2.5, 0 -1, 0 2, 1 6.3, 1 4.1, 0 3.3, 1 Thanks, Saeed --- R 2.8.1 Win XP Pro SP2 ROCR package v1.0-2 e1071 v1.5-19 ______________________________________________ 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.
