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.

the bad

Submitted by reference

combination of reference models, selected according to the validation set BER.

Dataset Balanced Error Area Under Curve  
Train Valid Test Train Valid Test
ada 0.1464 0.1806 0.1805 0.9392 0.893 0.9097 agnostic
gina 0 0.0253 0.0333 1 0.9968 0.9939 agnostic
hiva 0.0158 0.2467 0.273 0.999 0.7486 0.7742 agnostic
nova 0.0004 0.044 0.0481 1 0.9968 0.9894 agnostic
sylva 0.0023 0.0045 0.0078 0.9999 0.999 0.9988 agnostic
Overall 0.033 0.1002 0.1085 0.9876 0.9269 0.9332 agnostic