A Variational Approach for Learning from Positive and Unlabeled Data

1 code implementation • NeurIPS 2020 • Hui Chen, Fangqing Liu, Yin Wang, Liyue Zhao, Hao Wu

Learning binary classifiers only from positive and unlabeled (PU) data is an important and challenging task in many real-world applications, including web text classification, disease gene identification and fraud detection, where negative samples are difficult to verify experimentally.

Fraud Detection text-classification +1