Value of information in the binary case and confusion matrix

Belavkin, Roman V. ORCID logoORCID:, Pardalos, Panos M. and Principe, Jose C. (2022) Value of information in the binary case and confusion matrix. Physical Sciences Forum. Volume 5, Issue 1. In: The 41st International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, 18-22 July 2022, Paris, France. . [Conference or Workshop Item] (doi:10.3390/psf2022005008)

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The simplest Bayesian system used to illustrate ideas of probability theory is a coin and a boolean utility function. To illustrate ideas of hypothesis testing, estimation or optimal control, one needs to use at least two coins and a confusion matrix accounting for the utilities of four possible outcomes. Here we use such a system to illustrate the main ideas of Stratonovich’s value of information (VoI) theory in the context of a financial time-series forecast. We demonstrate how VoI can provide a theoretical upper bound on the accuracy of the forecasts facilitating the analysis and optimization of models.

Item Type: Conference or Workshop Item (Paper)
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Research Areas: A. > School of Science and Technology > Computer Science > Artificial Intelligence group
Item ID: 36712
Notes on copyright: Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
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Depositing User: Roman Belavkin
Date Deposited: 04 Nov 2022 10:23
Last Modified: 21 Nov 2022 15:57

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