Measuring Classification Decision Certainty and Doubt
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Authors
Bereneim, Alex
Cruickshank, Iain
Jha, Susmit
Thomson, Robert
Bastian, Nathaniel D.
Issue Date
2023-03-25
Type
Scholarly papers
Language
Keywords
stat.ML , cs.AI , cs.LG , math.DG , math.PR
Alternative Title
Abstract
Quantitative characterizations and estimations of uncertainty are of fundamental importance in optimization and decision-making processes. Herein,
we propose intuitive scores, which we call certainty and doubt, that can be used in both a Bayesian and frequentist framework to assess and compare the quality and uncertainty of predictions in (multi-)classification decision machine learning problems.
Description
Citation
Berenbeim, Alexander M., Iain J. Cruickshank, Susmit Jha, Robert H. Thomson, and Nathaniel D. Bastian. "Measuring classification decision certainty and doubt." arXiv preprint arXiv:2303.14568 (2023).
Publisher
Arxiv