Research and implement of classification rule mining algorithm based on attribute reduction

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper brings up a new classification algorithm of data mining (CRMA) in any scale relation database. Based on Rough set theory it divides relation table into several equivalence class based on attribute values, calculates information capacity in decision factor of the every condition attribution, eliminates redundancy attributions, and erases repeat units. Then classification rules can be obtained through strong equivalence class which relation table was reduced. It overcomes the redundancy nature, complicated nature and unfit nature to big capacity data or increment data of some classification algorithm at present. It has higher efficiency and widespread application perspective in large and incremental databases. The mining algorithm and an example are discussed in details.

Original languageEnglish
Title of host publication2007 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2007
PublisherIEEE Computer Society
Pages5601-5604
Number of pages4
ISBN (Print)1424413125, 1424413125, 9781424413126, 9781424413126
DOIs
StatePublished - 2007
Event2007 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2007 - Shanghai, China
Duration: 21 Sep 200725 Sep 2007

Publication series

Name2007 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2007

Conference

Conference2007 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2007
Country/TerritoryChina
CityShanghai
Period21/09/0725/09/07

Keywords

  • Attribute reduction
  • Classification rule
  • Condition attribute
  • Data mining
  • Decision-making attribute

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