PASCAL Agnostic Learning
vs.
Prior Knowledge
IJCNN07

The challenge is now over. But it remains open for post-challenge submissions!


IMPORTANT: Entries made since February 1st 2007 might be using validation data, now available for training.

TMK

Submitted by The Machine

TMK

B=1
GSection = 1

models: boosted trees

Dataset Balanced Error Area Under Curve  
Train Valid Test Train Valid Test
ada 0.1736 0.2177 0.1941 0.9177 0.8698 0.9017 agnostic
gina 0 0.0477 0.0617 1 0.9914 0.9844 agnostic
hiva 0.1222 0.2442 0.2967 0.9562 0.7902 0.7682 agnostic
nova 0.0251 0.108 0.1029 0.9973 0.955 0.9548 agnostic
sylva 0.0041 0.0111 0.0075 0.9998 0.9992 0.9989 agnostic
Overall 0.065 0.1257 0.1326 0.9742 0.9211 0.9216 agnostic

This entry is a complete agnostic learning entry.