How to train and apply one-class SVM?
I noticed, there is a One-Class SVM Classifier method in the LibSVM Operator. I guess this is for training only one-class (and adapting the specific ranges / Distributions) for this class..
how do I train one class, and then apply them for later classification?
e.g I train 3 classes, each with a one-class SVM.
In the later, I want to classify those 3 classes on a dataset with all 3 classes in it, would I have to use 3 SVM Classifier Models to do that? And how can one model then cope with the other 2 classes? how does it do that? Does it just check if a class falls in the distribution of the trained classes, and then decides if yes (it is the same class) or no?
and how can I design my process to use all the 3 trained One-Class SVM's onto one dataset with all 3 classes?