B-SVM employs a single transition threshold α min for the entire corpus, instead of a different threshold α x min for each x ∈ D. It is representative of the state-of-the-art for learning classifiers from PU data.
we propose as an alternative the use of Lazy Associative Classifiers (Veloso et al., 2006).