most citedImproving Positive Unlabeled Learning: Practical AUL Estimation and New Training Method for Extremely Imbalanced Data Sets

7 citations · 7 across the 1 of their papers we have counts for

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1 paper

cs.LG2020★ 7 cited

Improving Positive Unlabeled Learning: Practical AUL Estimation and New Training Method for Extremely Imbalanced Data Sets

Liwei Jiang, Dan Li, Qisheng Wang +2

Positive Unlabeled (PU) learning is widely used in many applications, where a binary classifier is trained on the datasets consisting of only positive and unlabeled samples. In thi…