DocumentCode
525766
Title
Retrieving classification rules based on indiscernibility relation
Author
Song, Baowei ; Zhang, Baowei ; Wei, Chunxue
Author_Institution
Sch. of Comput. & Commun. Eng., Zheng Zhou Univ. of Light Ind., Zheng Zhou, China
Volume
2
fYear
2010
fDate
12-13 June 2010
Firstpage
200
Lastpage
202
Abstract
A novel algorithm to mine classification rules based on the importance of attribute value is supposed. This algorithm views the importance as the number of tuple pair that can be discernible by the attribute, and the rules obtained from the constructed decision tree is equivalent to those obtained from ID3, which can be proved by the idea of rule fusion. However this method is of low computation, and is more suitable to large database.
Keywords
data mining; decision trees; pattern classification; ID3; attribute value importance; classification rules mining; classification rules retrieval; decision tree; indiscernibility relation; rule fusion; Aging; Educational institutions; decision rules; decision tree; rough set; rule fusion;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Communication Technologies in Agriculture Engineering (CCTAE), 2010 International Conference On
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6944-4
Type
conf
DOI
10.1109/CCTAE.2010.5543257
Filename
5543257
Link To Document