Hello all, I understand that maximum entropy models are excellent at categorizing documents. As it turns out, I have a situation where 1 document can be in many categories (1:m relationship). I believe that I could create training data that looks something like:
category_1 <text> category_2 <text> ... If I do this, will the resulting probability model return category probabilities as Pr(<text> in category_m) = 1/m for all categories m or it return Pr(<text> in category_m) = 1 for all categories m? This is a very important distinction. I really hope it is the later. If it isn't, do you have a way to make sure that if I receive a text that is similar to the training data, I can get a probability close to 1 if it fits into multiple categories? Thanks, ~Ben
