Then, its corresponding risk defined inR is If is not upper bounded, to achieve a small value of From this analysis, we can expect that, when using a unbounded loss function and a flexible classifier,R will dramatically decrease to a far below zero value.
in this work, we force to be bounded by replacing the common unbounded cross entropy loss function with the mean absolute error, resulting in a bounded unbiased positiveunlabeled learning (buPU) algorithm.