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arXiv · 2006.09046

Probabilistic Decoupling of Labels in Classification

Jeppe Nørregaard·Lars Kai Hansen
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Abstract

In this paper we develop a principled, probabilistic, unified approach to non-standard classification tasks, such as semi-supervised, positive-unlabelled, multi-positive-unlabelled and noisy-label learning. We train a classifier on the given labels to predict the label-distribution. We then infer the underlying class-distributions by variationally optimizing a model of label-class transitions.

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BibTeXRIS

Jeppe Nørregaard, Lars Kai Hansen. 2020-06-16. Probabilistic Decoupling of Labels in Classification. https://arxiv.org/abs/2006.09046

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