Specified Certainty Classification, with Application to Read Classification for Reference-Guided Metagenomic Assembly

Specified Certainty Classification (SCC) 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 cert...

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Detalles Bibliográficos
Autores principales: Karr, Alan F., Hauzel, Jason, Menon, Prahlad, Porter, Adam A., Schaefer, Marcel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cornell University 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8452099/
https://www.ncbi.nlm.nih.gov/pubmed/34545333
Descripción
Sumario:Specified Certainty Classification (SCC) 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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