Currently, SVMs don't have built-in multiclass support. Logistic
Regression supports multiclass, as do trees and random forests. It would
be great to add multiclass support for SVMs as well.
There is some ongoing work on generic multiclass-to-binary reductions:
https://issues.apache.org/jira/bro
Hi Robert,
I would say, taking the sign of the numbers represent the class of the
input-vector. What kind of data are you using, and what kind of traning-set
do you use. Fundamentally a SVM is able to separate only two classes, you
can do one vs the rest as you mentioned.
I don't see how LVQ can
