[R] repeated execution of svm(e1071) gives different results, if probability = TRUE is set

[Valdas]

Hello, Connoisseurs!

Please explain to novices, why svm model gives different results in the
loop with the same data? As a result, I can not find the best gamma and
cost parameters. Also tune.svm yields results that can not be repeated.
How can I avoid this?

My sessionInfo:
R version 2.11.1 (2010-05-31) 
x86_64-pc-linux-gnu 

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=C              LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods
base     

other attached packages:
[1] e1071_1.5-26 class_7.3-2 

Here's a simple code example. You can run it a few times.


library('e1071')

prob <- function() {
 model <- svm(Species ~ ., data = iris[-1,], probability=TRUE)
 p <- predict(model, newdata=iris[1,], probability=TRUE)
 pr <- attr(p, "probabilities")
 print(pr)
 return(pr)
}

cat('FirstCalc==SecondCalc:',all( prob() == prob() ),'\n')

Valdas