Accounting for label shift of positive unlabeled data under selection bias - Mielniczuk, Jan; Wawrzeńczyk, Adam (Zielona Góra: Uniwersytet Zielonogórski)
We consider the scenario when two samples of positive unlabeled (PU) data are available and for the second sample the change in prior probability of classes occurs while distributions of predictors in classes remain the same (label shift setting). The selection of positive elements may be object-dependent.
Keywords: positive unlabeled learning; label shift; augmented positive unlabeled data; selection bias; Bayes classifier; accuracy