02 Feb 2005
This is a small addendum to my talk to the Ana Group. Bill Atwood pointed out that the evaluation of the decision tree was flawed; it used the same data to evaluate the separation as was used to create the tree. This is bad since the procedure is sensitive to the training set.
I responded that I had limited nodes to have at least 100 events, but did not know the answer to his question. So here are some results. I train on only the even events in the all_gamma data set, then run the evaluation on three data sets:
The plot follows: