Re: [R] kernlab | ksvm error

2012-08-27 Thread Uwe Ligges
On 26.08.2012 15:33, Reza Salimi-Khorshidi wrote: Thanks Uwe, Am I right that in ksvm's internal cross-validation, there is no guarantee for having *at least one* of each classes in each subset? That is my guess, but I haven't read the code. Please read it yourself in case you want more det

Re: [R] kernlab | ksvm error

2012-08-26 Thread Reza Salimi-Khorshidi
Thanks Uwe, Am I right that in ksvm's internal cross-validation, there is no guarantee for having *at least one* of each classes in each subset? Some randomness is involved, and when you get an unfortunate subsample > (e.g. if in the internal cross-validation one class is not selected at all) > it

Re: [R] kernlab | ksvm error

2012-08-26 Thread Uwe Ligges
On 25.08.2012 02:12, Reza Salimi-Khorshidi wrote: Dear Uwe, I appreciate that if you let me know why, when using the attached file, the following script (two lines) doesn't work once in 10s of times. Best, Reza svm.pol4<- ksvm(class.labs~ ., data= train.data, prob.model= T, scale= T, kernel= "

Re: [R] kernlab | ksvm error

2012-08-24 Thread Reza Salimi-Khorshidi
Dear Uwe, I appreciate that if you let me know why, when using the attached file, the following script (two lines) doesn't work once in 10s of times. Best, Reza svm.pol4 <- ksvm(class.labs ~ ., data = train.data, prob.model = T, scale = T, kernel = "polydot") svm.pol.prd4 <- predict(svm.pol4, tra

Re: [R] kernlab | ksvm error

2012-08-19 Thread Reza Salimi-Khorshidi
Hi Uwe, I can attach the data file to an email or send you a link so you can download it. Which one do you prefer? Thanks for your help ... Best, Reza On Sun, Aug 19, 2012 at 4:10 PM, Uwe Ligges wrote: > > > On 19.08.2012 11:06, Reza Salimi-Khorshidi wrote: > >> Dear list, >> I am using the ksv

Re: [R] kernlab | ksvm error

2012-08-19 Thread Uwe Ligges
On 19.08.2012 11:06, Reza Salimi-Khorshidi wrote: Dear list, I am using the ksvm function from kernlab as follows: (1) learning svm.pol4 <- ksvm(class.labs ~ ., data = train.data, prob.model = T, scale = T, kernel = "polydot") (2) prediction svm.pol.prd4 <- predict(svm.pol4, train.data, ty

[R] kernlab | ksvm error

2012-08-19 Thread Reza Salimi-Khorshidi
Dear list, I am using the ksvm function from kernlab as follows: (1) learning > svm.pol4 <- ksvm(class.labs ~ ., data = train.data, prob.model = T, scale = T, kernel = "polydot") (2) prediction > svm.pol.prd4 <- predict(svm.pol4, train.data, type = "probabilities")[,2] But unfortunately, when ca