[R] multiclass SVM (e1071 package): number of estimated models
Dear John, there *are* indeed 3 classifiers trained, as you can see from predict(model, iris, decision.values = TRUE) However, the coefficients are stored in a compressed format -- see svminternals.txt in the /doc subdirectory. Best David - I run multiclass SVM for iris data, which contains 3 classes (manual page 52). Based on manual, the implementation uses one-against-one approach: k*(k-1)/2 binary classifiers trained. However, I am getting only two models instead of three (only two columns of support vectors and coefficients). What do I miss? __ R-help@r-project.org 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] multiclass SVM (e1071 package): number of estimated models
Hi, I run multiclass SVM for iris data, which contains 3 classes (manual page 52). Based on manual, the implementation uses one-against-one approach: k*(k-1)/2 binary classifiers trained. However, I am getting only two models instead of three (only two columns of support vectors and coefficients). What do I miss? Thanks a lot for help, John Bellow is the code. package(e1071) data(iris) x <- subset(iris, select = -Species) y <- Species model <- svm(x, y) model$SV model$coefs -- View this message in context: http://www.nabble.com/multiclass-SVM-%28e1071-package%29%3A-number-of-estimated-models-tp25624020p25624020.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org 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.
