Hi everyone, I am new to OpenNLP maxent classifier, and I have a question regarding using features that are label-dependent.
I have two sets of words (S1 and S2, where ||S1|| >> ||S2||), and I am trying to create find words from S2 that are most similar to S1 using features I designed. I turned this into a classification problem, treating words from S2 as labels, and built a nice training set. However, my features are dependent on the labels itself. I can't find a simple way in OpenNLP to utilize labels in the prediction process. My guess is I would have to subclass MaxentModel and implement eval() method? Is there an easier way to solve this problem? Or perhaps, maximum entropy is not the best algorithm of choice? Thanks, George
