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dc.contributor.authorNevill-Manning, Craig G.
dc.contributor.authorHolmes, Geoffrey
dc.contributor.authorWitten, Ian H.
dc.date.accessioned2008-10-21T00:19:03Z
dc.date.available2008-10-21T00:19:03Z
dc.date.issued1995-06
dc.identifier.citationNevill-Manning, C. G., Holmes, G. & Witten, I. H.(1995) The development of Holte's 1R Classifier. (Working paper 95/19). Hamilton, New Zealand: University of Waikato, Department of Computer Science.en_US
dc.identifier.issn1170-487X
dc.identifier.urihttps://hdl.handle.net/10289/1096
dc.description.abstractThe 1R procedure for machine learning is a very simple one that proves surprisingly effective on the standard datasets commonly used for evaluation. This paper describes the method and discusses two areas that can be improved: the way that intervals are formed when discretizing continuously-valued attributes, and the way that missing values are treated. Then we show how the algorithm can be extended to avoid a problem endemic to most practical machine learning algorithms—their frequent dismissal of an attribute as irrelevant when in fact it is highly relevant when combined with other attributes.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherUniversity of Waikato, Department of Computer Scienceen_US
dc.relation.ispartofseriesComputer Science Working Papers
dc.subjectcomputer scienceen_US
dc.titleThe development of Holte's 1R Classifieren_US
dc.typeWorking Paperen_US
uow.relation.series95/19


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