Paper ID: 2210.08576

Skeptical inferences in multi-label ranking with sets of probabilities

Yonatan Carlos Carranza Alarcón, Vu-Linh Nguyen

In this paper, we consider the problem of making skeptical inferences for the multi-label ranking problem. We assume that our uncertainty is described by a convex set of probabilities (i.e. a credal set), defined over the set of labels. Instead of learning a singleton prediction (or, a completed ranking over the labels), we thus seek for skeptical inferences in terms of set-valued predictions consisting of completed rankings.

Submitted: Oct 16, 2022