I am trying to classify legal case documents which are in text format, in different folders like Civil, Land, Criminal, e.t.c, I intended using Naive Bayes as Vectoriser to get the vectors from the text documents,feed it in to SVM to classify the documents using javaml, I have implemented the preprocessing like stemming, I used the formulars of Naive Bayes as seen in http://eprints.nottingham.ac.uk/2995/1/Isa_Text.pdf to calculate prior probability, likelihood, evidence and posterior probability, I am assuming the posterior probability is the vector to be fed into SVM, but I cannot format the output to feed into the SVM library.
I need all the help I can get in this, I hope I am doing things right.
I have other legal cases as test set that I want to classify to the right categories.