Simplifying Decision Trees

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6453

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DC Field	Value	Language
dc.creator	Quinlan, J.R.	-
dc.date	2004-10-04T14:56:58Z	-
dc.date	2004-10-04T14:56:58Z	-
dc.date	1986-12-01	-
dc.date.accessioned	2013-10-09T02:45:31Z	-
dc.date.available	2013-10-09T02:45:31Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-930	-
dc.identifier	http://hdl.handle.net/1721.1/6453	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	Many systems have been developed for constructing decision trees from collections of examples. Although the decision trees generated by these methods are accurate and efficient, they often suffer the disadvantage of excessive complexity that can render them incomprehensible to experts. It is questionable whether opaque structures of this kind can be described as knowledge, no matter how well they function. This paper discusses techniques for simplifying decision trees without compromising their accuracy. Four methods are described, illustrated, and compared on a test- bed of decision trees from a variety of domains.	-
dc.format	2415062 bytes	-
dc.format	953581 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-930	-
dc.title	Simplifying Decision Trees	-
Appears in Collections:	MIT Items

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