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.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.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.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 | |