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Skeptical inferences in multi-label ranking with sets of probabilities

2022/10/16 by Yonatan Carlos Carranza Alarcón, Alarcón, Yonatan Carlos Carranza, Vu-Linh Nguyen +1
Computer Science · #Machine Learning and Algorithms #Bayesian Modeling and Causal Inference #Machine Learning and Data Classification

paper · pdf · doi:10.48550/arxiv.2210.08576

Abstract

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.

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