I am trying to classify customer support sessions using supervised machine learning.
In each customer support session I have 3 bags of information. 1. The title of the customer's complaint 2. Information about the device the customer was using 3. Text of the chat session with the customer support agent
In each customer support session, there are 6 different classes. Is it better to: 1. Train a classifier on each bag of information and have them vote on which class the session belongs to? 2. Put all of the information into a single set of features, and train a single classifier to determine which class the session belongs to? 3. Other?