Boost Picking: A Universal Method on Converting Supervised Classification to Semi-supervised Classification

Fuqiang Liu, Fukun Bi, Yiding Yang +1

This paper proposes a universal method, Boost Picking, to train supervised classification models mainly by un-labeled data. Boost Picking only adopts two weak classifiers to estima…