Ai Dreams Forum
Member's Experiments & Projects => General Project Discussion => Topic started by: samuelchvez on December 10, 2012, 05:03:25 pm
-
Hi guys, I'm working in an automated product labeler that should work as follows:
Given a set of indicators (keywords) for a given product, infere what kind of product it is (label it).
I've managed to get almost 8000 string keywords, 500 string labels, and almost 5000 supervised training cases (set(keyword) -> label), and I was willing to use Java Weka / Mulan for this task.
The problem is that my trainer program has been runing for more than 6 hours and it has not yet completed the training ... I need a simplier approach to succeed at this task.
Any insights / ideas?