How to : What to do when your model fails?
July 25th, 2009
3 comments
Sometimes (well most of the time) using your favorite data mining methods and the more obvious attributes are not good enough. What to do then? An usual idea is to use every other models your software provides and/or add every attributes you could think of whatever their relation to your problem. In this post, I will try to elaborate a kind of “how to” for this case.
Step 1 : What is my model?
If your model is a neural network, it’s quite hard to get any insight of how it works by looking at the weights or neural functions. How could you improve something you don’t understand?