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Optimal probability aggregation based on generalized brier scoring

Optimal probability aggregation based on generalized brier scoring In this paper we combine the theory of probability aggregation with results of machine learning theory concerning the optimality of predictions under expert advice. In probability aggregation theory several characterization results for linear aggregation exist. However, in linear aggregation weights are not fixed, but free parameters. We show how fixing such weights by success-based scores, a generalization of Brier scoring, allows for transferring the mentioned optimality results to the case of probability aggregation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Mathematics and Artificial Intelligence Springer Journals

Optimal probability aggregation based on generalized brier scoring

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References (20)

Publisher
Springer Journals
Copyright
Copyright © Springer Nature Switzerland AG 2019
Subject
Computer Science; Artificial Intelligence; Mathematics, general; Computer Science, general; Complex Systems
ISSN
1012-2443
eISSN
1573-7470
DOI
10.1007/s10472-019-09648-4
Publisher site
See Article on Publisher Site

Abstract

In this paper we combine the theory of probability aggregation with results of machine learning theory concerning the optimality of predictions under expert advice. In probability aggregation theory several characterization results for linear aggregation exist. However, in linear aggregation weights are not fixed, but free parameters. We show how fixing such weights by success-based scores, a generalization of Brier scoring, allows for transferring the mentioned optimality results to the case of probability aggregation.

Journal

Annals of Mathematics and Artificial IntelligenceSpringer Journals

Published: Jul 20, 2020

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