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Classification ensemble methods for mitigating concept drift within online data streams

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dc.contributor.authorBarber, Michael J., author
dc.contributor.authorHowe, Adele E., advisor
dc.contributor.authorAnderson, Charles, committee member
dc.contributor.authorHoeting, Jennifer, committee member
dc.date.accessioned2007-01-03T08:10:34Z
dc.date.available2007-01-03T08:10:34Z
dc.date.issued2012
dc.description.abstractThe task of instance classification within very large data streams is challenged by both the overwhelming amount of data, and a phenomenon known as concept drift. In this research we provide a comprehensive comparison of several state of the art ensemble methods that purport to handle concept drift, and we propose two additional algorithms. Our two new methods, the AMPE and AMPE2 algorithms are then used to further our understanding of concept drift and the algorithmic factors that influence the performance of ensemble based concept drift algorithms.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.identifierBarber_colostate_0053N_11127.pdf
dc.identifierETDF2012500144COMS
dc.identifier.urihttp://hdl.handle.net/10217/67994
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rights.licenseThis material is open access and distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0).
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectdata mining
dc.subjectonline analysis
dc.subjectmachine learning
dc.subjectensembles
dc.titleClassification ensemble methods for mitigating concept drift within online data streams
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineComputer Science
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)

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