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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Bibliographic Details
Published in:arXiv.org 2021-09
Main Authors: Karr, Alan F, Hauzel, Jason, Menon, Prahlad, Porter, Adam A, Schaefer, Marcel
Format: Article
Language:English
Subjects:
Assembly
Classification
Classifiers
Decisions
Online Access:Get full text
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Description
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.
ISSN:2331-8422