IQuickReduct: An improvement to quick reduct algorithm

dc.contributor.author	Sai Prasad, P. S.V.S.
dc.contributor.author	Rao, C. Raghavendra
dc.date.accessioned	2022-03-27T06:00:11Z
dc.date.available	2022-03-27T06:00:11Z
dc.date.issued	2009-12-01
dc.description.abstract	Most of the Rough Sets applications are involved in conditional reduct computations. Quick Reduct Algorithm (QRA) for reduct computation is most popular since its discovery. The QRA has been modified in this paper by sequential redundancy reduction approach. The performance of this new improved Quick Reduct (IQRA) is discussed in this paper. © 2009 Springer-Verlag Berlin Heidelberg.
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). v.5908 LNAI
dc.identifier.issn	03029743
dc.identifier.uri	10.1007/978-3-642-10646-0_18
dc.identifier.uri	http://link.springer.com/10.1007/978-3-642-10646-0_18
dc.identifier.uri	https://dspace.uohyd.ac.in/handle/1/9069
dc.subject	Feature Selection
dc.subject	Quick Reduct
dc.subject	Reduct
dc.subject	Redundancy
dc.subject	Rough Sets
dc.subject	Variable Precision Rough Sets
dc.title	IQuickReduct: An improvement to quick reduct algorithm
dc.type	Book Series. Conference Paper
dspace.entity.type

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