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.

EI+NB

Submitted by Vladimir Nikulin

Naive-Bayes for HIVA

Dataset Balanced Error Area Under Curve  
Train Valid Test Train Valid Test
ada 0.1757 0.1948 0.1916 0.8239 0.8022 0.7968 agnostic
gina 0 0.038 0.0574 1 0.9682 0.9496 agnostic
hiva 0.2155 0.3319 0.3076 0.7887 0.6185 0.6994 agnostic
nova 0.0114 0.044 0.0614 0.9901 0.964 0.9367 agnostic
sylva 0.0066 0.0049 0.0087 0.9962 0.9983 0.9966 agnostic
Overall 0.0818 0.1227 0.1253 0.9198 0.8703 0.8758 agnostic

This entry is a complete agnostic learning entry.