I am facing a problem on selecting a correct classifier for my data-mining task.
I am labeling webpages using statistical method and label them using a 1-4 scale, 1 being the poorest while 4 being the best.
Previously, I used SVM to train the system since I was using a binary (1,0) label then. But now since I switch to this 4-class label, I need to change classifier, because I think the SVM classifier will only work for two-class classification (correct me if I am wrong).
What kind of classifier is most appropriate here for my classification purpose?
There exist multi-class SVMs. LibSVM has an implementation, as does Weka.
Usually it's better to experiment with several classifiers to find out which one works best on your data. The choice of classifier type and training algorithm is far less important than your choice of feature set. You could try naïve Bayes, multi-class SVM, MaxEnt, voted perceptrons, or whatever your library offers.