The development of Holte's 1R Classifier

dc.contributor.author	Nevill-Manning, Craig G.
dc.contributor.author	Holmes, Geoffrey
dc.contributor.author	Witten, Ian H.
dc.date.accessioned	2008-10-21T00:19:03Z
dc.date.available	2008-10-21T00:19:03Z
dc.date.issued	1995-06
dc.description.abstract	The 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.mimetype	application/pdf
dc.identifier.citation	Nevill-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.issn	1170-487X
dc.identifier.uri	https://hdl.handle.net/10289/1096
dc.language.iso	en
dc.publisher	University of Waikato, Department of Computer Science	en_US
dc.relation.ispartofseries	Computer Science Working Papers
dc.subject	computer science	en_US
dc.subject	Machine learning
dc.title	The development of Holte's 1R Classifier	en_US
dc.type	Working Paper	en_US
uow.relation.series	95/19