Multiple feature vectors in weka

Question

I am working in a Text categorization project using Weka,I have 12 class I need to find text keywords for each class that distinguish one class from others, So I am thinking to make feature vector(FV) for each class independently and store 12 (FV)s in separated 12 arff files!

The Question Is --> How can I combine 12 different Feature vectors in one feature vector?

Answer 1

Depending on classes overlapping or not, I propose two different approaches instead of joining the feature vectors:

• If classes are not overlapping (that is, no document is in two or more classes at the same time), you would rather build a single ARFF file and then make use of the AttributeSelection filter (Ranker search, InfoGainAttributeEval evaluator suggested) to determine which features most discriminate among all the classes.

• If classes are overlapping, you could build twelve one-again-the-rest classifiers, each one with its own vocabulary. You could apply attribute selection to each independent problem as well, finding the features that best discriminate a single class from all of the rest.