Hi, I have been using Open NLP for a while now. I have been training models with custom data along with predefined features as well as custom features. Could someone explain me/ guide me to some documentation of what is happening internally.
The thing I am particularly interested are : 1. What is happening during each iteration ? 2. How the log likelihood and probability is calculated at each step ? 3. How a test case is classified ? 4. What happens during training ? 5. How Maximum entropy works ? Someone please guide me. Thanks. Manoj
