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
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;
Conference_Titel :
Computer and Communication Technologies in Agriculture Engineering (CCTAE), 2010 International Conference On
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6944-4
DOI :
10.1109/CCTAE.2010.5543257
