If your question is "Can we set the relative importance of features for classification using an OpenNLP interface," I believe the answer is that there isn't.
But if your question is, "Can we set the relative importance of features for classification using some means?" then the answer is yes. You can do it by repeating the feature the required number of times in your training file. Eg: *CLASS2* token1 token2 token3 token4^2 can be written as *CLASS2* token1 token2 token3 token4 token4 I don't know if this will lead to any performance improvements in the case of the maxent classification algorithm, but if done right, it could improve the performance with naive bayes. Cohan On Sun, Jul 30, 2017 at 7:14 PM, Damiano Porta <[email protected]> wrote: > anyone? > > 2017-07-26 18:14 GMT+02:00 Damiano Porta <[email protected]>: > > > Hello, > > I would like to boost specific features/tokens on the training set. Can i > > set the weights somehow? > > Something like: > > > > *CLASS1* token1^10 token2 token3^5 > > *CLASS2* token1 token2 token3 token4^5 > > > > Thanks > > Damiano > > >
