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Specified Certainty Classification, with Application to Read Classification for Reference-Guided Metagenomic Assembly
Specified Certainty Classification (SCC) is a new paradigm for employing classifiers whose outputs carry uncertainties, typically in the form of Bayesian posterior probabilities. By allowing the classifier output to be less precise than one of a set of atomic decisions, SCC allows all decisions to a...
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Published in: | ArXiv.org 2021-09 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Online Access: | Get full text |
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Summary: | Specified Certainty Classification (SCC) is a new paradigm for employing classifiers whose outputs carry uncertainties, typically in the form of Bayesian posterior probabilities. By allowing the classifier output to be less precise than one of a set of atomic decisions, SCC allows all decisions to achieve a specified level of certainty, as well as provides insights into classifier behavior by examining all decisions that are possible. Our primary illustration is read classification for reference-guided genome assembly, but we demonstrate the breadth of SCC by also analyzing COVID-19 vaccination data. |
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ISSN: | 2331-8422 |