--Hi I know that there are some discussion about the use of MaxEnt with real-valued features out there but this question is about its performance.
So, I used MaxEnt with binary features in some problems (multiclass classification problems such as NER) and it worked quite well in terms of performance (accuracy, F-measures...). I recently want to add some real valued features to the systems. So, my feature set will include both binary and real-valued features. In principle, we can do it in MaxEnt package by assigning binary features with the values of 1 and keeping the real-valued features unchanged. However, I wonder if this would be helpful for the final performance. Have anybody tried this before? Any suggestion would be appreciated. Thank you very much.
