DocumentCode
3511106
Title
Research and Implement of Classification Rule Mining Algorithm Based on Attribute Reduction
Author
Yin, Shiqun ; Qiu, Yuhui ; Zhong, Chengwen ; Zhou, Jifu
Author_Institution
Fac. of Comput. & Inf. Sci., Southwest Univ., Chongqing
fYear
2007
fDate
21-25 Sept. 2007
Firstpage
5601
Lastpage
5604
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.
Keywords
classification; data mining; relational databases; rough set theory; attribute reduction; classification rule mining algorithm; data mining; decision factor; equivalence class; relation database; rough set theory; Classification algorithms; Classification tree analysis; Data mining; Databases; Decision making; Electronic mail; High performance computing; Information science; Iterative algorithms; Set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-1311-9
Type
conf
DOI
10.1109/WICOM.2007.1372
Filename
4341147
Link To Document