Efficient attribute reduction based on discernibility matrix

Xu, Z; Zhang, C; Zhang, S; Song, W; Yang, B

Efficient attribute reduction based on discernibility matrix

Xu, Z Zhang, C

Zhang, S Song, W Yang, B

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, 4481 LNAI pp. 13 - 21
Issue Date:: 2007-12-24

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Field	Value	Language
dc.contributor.author	Xu, Z	en_US
dc.contributor.author	Zhang, C https://orcid.org/0000-0001-5715-7154	en_US
dc.contributor.author	Zhang, S	en_US
dc.contributor.author	Song, W	en_US
dc.contributor.author	Yang, B	en_US
dc.date.issued	2007-12-24	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, 4481 LNAI pp. 13 - 21	en_US
dc.identifier.isbn	9783540724575	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/1729
dc.description.abstract	To reduce the time complexity of attribute reduction algorithm based on discernibility matrix, a simplified decision table is first introduced, and an algorithm with time complexity O(\| C ∥ U \|) is designed for calculating the simplified decision table. And then, a new measure of the significance of an attribute is defined for reducing the search space of simplified decision table. A recursive algorithm is proposed for computing the attribute significance that its time complexity is of 0(\|U/C\|). Finally, an efficient attribute reduction algorithm is developed based on the attribute significance. This algorithm is equal to existing algorithms in performance and its time complexity is O(\| C ∥r U \|) +O(\| C \|2\| / C \|). © Springer-Verlag Berlin Heidelberg 2007.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Efficient attribute reduction based on discernibility matrix	en_US
dc.type	Conference Proceeding
utslib.citation.volume	4481 LNAI	en_US
utslib.for	080704 Information Retrieval and Web Search	en_US
utslib.for	080604 Database Management	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
dc.location.activity	Canada	en_US
dc.location.activity	Sydney, Australia
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (International)
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - ACRI - Australia China Relations Institute
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	4481 LNAI	en_US

Abstract:

To reduce the time complexity of attribute reduction algorithm based on discernibility matrix, a simplified decision table is first introduced, and an algorithm with time complexity O(| C ∥ U |) is designed for calculating the simplified decision table. And then, a new measure of the significance of an attribute is defined for reducing the search space of simplified decision table. A recursive algorithm is proposed for computing the attribute significance that its time complexity is of 0(|U/C|). Finally, an efficient attribute reduction algorithm is developed based on the attribute significance. This algorithm is equal to existing algorithms in performance and its time complexity is O(| C ∥r U |) +O(| C |2| / C |). © Springer-Verlag Berlin Heidelberg 2007.

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http://hdl.handle.net/10453/1729