A mathematical framework for statistical decision confidence

BioRxiv : the Preprint Server for Biology
Balázs HangyaAdam Kepecs

Abstract

Decision confidence is a forecast about the probability that a decision will be correct. For human decision makers, confidence is a deeply subjective sense that can be difficult to study due to its inherently introspective nature. However, confidence can be framed as an objective mathematical quantity – the Bayesian posterior probability, providing a formal definition of statistical decision confidence. Here we use this definition as a starting point to develop a normative statistical framework for decision confidence. We analytically prove interrelations between statistical decision confidence and other observable decision measures. Among these is a counterintuitive property of confidence – that the lowest average confidence occurs when classifiers err in the presence of the strongest evidence. These results lay the foundations for a mathematically rigorous treatment of decision confidence that can lead to a common framework for understanding confidence across different research domains, from human behavior to neural representations.

Related Concepts

Classification
Objective (Goal)
Research
Dorsal
Self Confidence
Decision
Neural Stem Cells
Definition

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