Hi, I am using the MLlib Naive Bayes for a text classification problem. I have very less amount of training data. And then the data will be coming continuously and I need to classify it as either A or B. I am training the MLlib Naive Bayes model using the training data but next time when data comes, I want to predict its class and then incorporate that also in the model for next time prediction of new data(I think that is obvious).
So I am not able to figure out what is the way to do that using MLlib Naive Bayes. Is it that I have to train the model on the whole data every time new data comes in?? Thanks in Advance! -- Rahul K Bhojwani 3rd Year B.Tech Computer Science and Engineering National Institute of Technology, Karnataka
