Making Likelihood Ratios Digestible for Cross-Application Performance Assessment
| Autor: | Jonas Lindh, Daniel Ramos, Andreas Nautsch, Didier Meuwly, Christoph Busch |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science Applied Mathematics 010401 analytical chemistry Probability density function Bayes decision framework Machine learning computer.software_genre binary decisions 01 natural sciences Interchangeability biometric verification 0104 chemical sciences 03 medical and health sciences Bayes' theorem detection error tradeoff (DET) 0302 clinical medicine Signal Processing verbal scales 030216 legal & forensic medicine Data mining Artificial intelligence Electrical and Electronic Engineering business computer |
| Zdroj: | IEEE signal processing letters, 24(10):17176768, 1552-1556. IEEE |
| ISSN: | 1070-9908 |
| DOI: | 10.1109/lsp.2017.2748899 |
| Popis: | Performance estimation is crucial to the assessment of novel algorithms and systems. In detection error tradeoff (DET) diagrams, discrimination performance is solely assessed targeting one application, where cross-application performance considers risks resulting from decisions, depending on application constraints. For the purpose of interchangeability of research results across different application constraints, we propose to augment DET curves by depicting systems regarding their support of security and convenience levels. Therefore, application policies are aggregated into levels based on verbal likelihood ratio scales, providing an easy to use concept for business-to-business communication to denote operative thresholds. We supply a reference implementation in Python, an exemplary performance assessment on synthetic score distributions, and a fine-tuning scheme for Bayes decision thresholds, when decision policies are bounded rather than fix. |
| Databáze: | OpenAIRE |
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