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WEKA−Experiences with a Java open-source project

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dc.contributor.authorBouckaert, Remco R.
dc.contributor.authorFrank, Eibe
dc.contributor.authorHall, Mark A.
dc.contributor.authorHolmes, Geoffrey
dc.contributor.authorPfahringer, Bernhard
dc.contributor.authorReutemann, Peter
dc.contributor.authorWitten, Ian H.
dc.date.accessioned2010-11-08T02:24:52Z
dc.date.available2010-11-08T02:24:52Z
dc.date.issued2010
dc.description.abstractWEKA is a popular machine learning workbench with a development life of nearly two decades. This article provides an overview of the factors that we believe to be important to its success. Rather than focussing on the software's functionality, we review aspects of project management and historical development decisions that likely had an impact on the uptake of the project.en_NZ
dc.identifier.citationBouckaert, R.R., Frank. E., Hall, M.A., Holmes, G., Pfahringer, B.,…, Witten, I.H. (2010). WEKA−Experiences with a Java open-source project. Journal of Machine Learning Research, 11, 2533-254.en_NZ
dc.identifier.urihttps://hdl.handle.net/10289/4766
dc.language.isoen
dc.publisherMicrotome Publishingen_NZ
dc.relation.isPartOfJournal of Machine Learning Researchen_NZ
dc.relation.urihttp://jmlr.csail.mit.edu/papers/v11/bouckaert10a.htmlen_NZ
dc.subjectmachine learning softwareen_NZ
dc.subjectopen source softwareen_NZ
dc.subjectMachine learning
dc.titleWEKA−Experiences with a Java open-source projecten_NZ
dc.typeJournal Articleen_NZ
dspace.entity.typePublication
pubs.begin-page2533en_NZ
pubs.end-page2541en_NZ
pubs.volume11en_NZ

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