A semi-supervised Spam mail detector
Bernhard Pfahringer · Research Commons (University of Waikato) · 2006
Abstract. This document describes a novel semi-supervised approach to spam classification, which was successful at the ECML/PKDD 2006 spam classification challenge. A local learning method based on lazy projections was successfully combined with a variant of a standard semisupervised learning algorithm. 1