Consider we have a binary SVM classifier, classifying event A and event B and we want to add another class (or more) say event C, to our SVM. Can we add C without using the training data of event A and B. Generally SVM is binary classifier so to use for more than one class we can use "1-against-the rest" or "1-against-1." For either of this method can I use only data from training of event C and the earlier SVM parameters of A and B, without data of A and B for training.
In my opinion we cannot train SVM with learned parameters alone we need data from A and B as well. The question is: is it true? I am looking for an article or mathematical reason?