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.

RBF SVM

Submitted by Vojtech Franc

RBF SVM, hyperparameters tuned using LOO BER

Dataset Balanced Error Area Under Curve  
Train Valid Test Train Valid Test
ada 0.1864 0.2239 0.2037 0.8975 0.8551 0.8835 agnostic
gina 0.0009 0.0445 0.0552 1 0.9923 0.9869 agnostic
hiva 0.1036 0.3027 0.2827 0.9652 0.7952 0.7707 agnostic
nova 0.0014 0.084 0.0877 1 0.9906 0.9834 agnostic
sylva 0.0088 0.018 0.0205 0.998 0.9984 0.9971 agnostic
Overall 0.0602 0.1346 0.13 0.9721 0.9263 0.9243 agnostic

This entry is a complete agnostic learning entry.