Generation of rough set (RS) significant reducts and rules for cardiac dataset classification

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Bibliographic Details
Main Author:	Sulaiman, Noor Suhana
Format:	Thesis
Published:	2007
Subjects:	QA75 Electronic computers Computer science
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id	my-utm-ep.2583
record_format	uketd_dc
spelling	my-utm-ep.25832013-11-13T04:40:59Z Generation of rough set (RS) significant reducts and rules for cardiac dataset classification 2007 Sulaiman, Noor Suhana QA75 Electronic computers. Computer science 2007 Thesis http://eprints.utm.my/id/eprint/2583/ masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Sulaiman, Noor Suhana Generation of rough set (RS) significant reducts and rules for cardiac dataset classification
description
format	Thesis
qualification_level	Master's degree
author	Sulaiman, Noor Suhana
author_facet	Sulaiman, Noor Suhana
author_sort	Sulaiman, Noor Suhana
title	Generation of rough set (RS) significant reducts and rules for cardiac dataset classification
title_short	Generation of rough set (RS) significant reducts and rules for cardiac dataset classification
title_full	Generation of rough set (RS) significant reducts and rules for cardiac dataset classification
title_fullStr	Generation of rough set (RS) significant reducts and rules for cardiac dataset classification
title_full_unstemmed	Generation of rough set (RS) significant reducts and rules for cardiac dataset classification
title_sort	generation of rough set (rs) significant reducts and rules for cardiac dataset classification
granting_institution	Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department	Faculty of Computer Science and Information System
publishDate	2007
_version_	1747814425337790464

Generation of rough set (RS) significant reducts and rules for cardiac dataset classification

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