Can anyone explain the root of my problem? When I type the following code into R, I receive 42 support vectors insted of the 21 stated in the book 'Modern Applied Statistics with S':
library(MASS); library(e1071); library(class); lcrabs <- log(crabs[,4:8]); (svm(crabs$sp ~ ., data = lcrabs, cost = 100, gamma = 1)); By changing the value of gamma I can obtain only 21 support vectors, but I not sure where an explanation to my problem can be found. I use R 2.3.2 and the most recent version of the package 'e1071'. My goal is to minimise the number of SVs for a separate data set. Many thanks, Graeme. ______________________________________________ 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.
