Hi- I'm seeing some weirdness with svm and tune.svm that I can't figure out- was wondering if anyone else has seen this? Perhaps I'm failing to make something the expected class? Below is my repro case, though it *sometimes* doesn't repro. I'm using R2.3.1 on WindowsXP. I was also seeing it happen with R2.1.1 and have seen it on 2 different machines. data(iris) attach(iris) library(e1071) train<- iris[c(1:30,50:80,100:130),] test<- iris[-c(1:30,50:80,100:130),] y.train<- train$Species y.test<- test$Species obj<- tune.svm(train[,-5], y.train, gamma = 2^(-1:1), cost = 2^(2:4), probability=T) my.svm<- obj$best.model pred1<- predict(my.svm, test[,-5]) pred2<- predict(my.svm, test[,-5], probability=T) table(pred1, y.test) table(pred2, y.test)
When I do this, the two different tables often come out different, as below: > table(pred1, y.test) y.test pred1 setosa versicolor virginica setosa 19 0 0 versicolor 0 18 1 virginica 0 1 19 > table(pred2, y.test) y.test pred2 setosa versicolor virginica setosa 18 0 0 versicolor 1 18 1 virginica 0 1 19 > I'm not sure 1. why the results would differ based on whether I choose to calculate the probabilities, and 2. which one to trust?? Anyone come across this before, or have any ideas? thanks, jessie ______________________________________________ R-help@stat.math.ethz.ch 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.