Tuesday, January 29, 2013

Overfitting in Computer Aided Diagnosis

I've just had the honour of having one of my journal papers published by invitation. The paper is on overfitting, a scourge of a problem for pattern recognition researchers. Overfitting is a problem that occurs when a learning machine is overly tuned to the data it was provided to learn on. Overfitting is a particularly problematic phenomenon as an overfitted classifier (or supervised learning algorithm) may yield extremely promising results on the data set being evaluated while simultaneously providing an unreliable test on new datasets that it has not yet been exposed to.