Majority Voting by Independent Classifiers Can Increase Error Rates
type: Item
instance of: scholarly article
title: Majority Voting by Independent Classifiers Can Increase Error Rates
DOI: 10.1080/00031305.2013.778788
author: Max D. Morris
author: Stephen B. Vardeman
published in: The American Statistician
publication date: 2023-02-03T00:00:00Z
Mathematics Subject Classification ID: 62-XX
zbMATH DE Number: 7649188
zbMATH Keywords: classifier fusion
zbMATH Keywords: Condorcet jury theorem
zbMATH Keywords: machine learning
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1080/00031305.2013.778788
OpenAlex ID: W2109178578
cites work: Random forests
cites work: A `No panacea theorem' for classifier combination
cites work: Combining Pattern Classifiers
cites work: Limits on the majority vote accuracy in classifier fusion
cites work: Q5483525
description: scientific article; zbMATH DE number 7649188