[R] training svm's with probability flag
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$best.model pred1- predict(my.svm, test[,-5]) pred2- predict(my.svm, test[,-5], probability=T) table(pred1, y.test) table(pred2, y.test) When I do this, the two different tables often come out different, as below: table(pred1, y.test) y.test pred1setosa versicolor virginica setosa 19 0 0 versicolor 0 18 1 virginica 0 119 table(pred2, y.test) y.test pred2setosa versicolor virginica setosa 18 0 0 versicolor 1 18 1 virginica 0 119 I'm not sure 1. why the results would differ based on whether I choose to calculate the probabilities, and 2. which one to trust?? Anyone come across this before, or have any ideas? thanks, jessie [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] training svm's with probability flag (re-send in plain text)
Hi- I'm seeing some weirdness with svm and tune.svm that I can't figure out- was wondering if anyone else has seen this? Perhaps I'm failing to make something the expected class? Below is my repro case, though it *sometimes* doesn't repro. I'm using R2.3.1 on WindowsXP. I was also seeing it happen with R2.1.1 and have seen it on 2 different machines. data(iris) attach(iris) library(e1071) train- iris[c(1:30,50:80,100:130),] test- iris[-c(1:30,50:80,100:130),] y.train- train$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 pred1setosa versicolor virginica setosa 19 0 0 versicolor 0 18 1 virginica 0 119 table(pred2, y.test) y.test pred2setosa versicolor virginica setosa 18 0 0 versicolor 1 18 1 virginica 0 119 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.
