TPN 2 : Using positive-only learning to deal with the heterogeneity of labeled and unlabeled data
Nikolaos Trogkanis, Γεώργιος Παλιούρας · 2006
Abstract. This paper introduces TPN 2, the runner up method in both tasks of the ECML-PKDD Discovery Challenge 2006 on personalized spam filtering. TPN 2 is a classifier training method that bootstraps positive-only learning with fully-supervised learning, in order to make the most of labeled and unlabeled data, under the assumption that the two are drawn from significantly different distributions. Furthermore, the unlabeled data themselves are separated into subsets that are assumed to be drawn from multiple distributions. For that reason, TPN 2 trains a different classifier for each subset, making use of all unlabeled data each time.