DocumentCode :
447567
Title :
LEM2-based rule induction via clustering decision classes
Author :
Inuiguchi, Masahiro ; Tsurumi, Masayo ; Fukuda, Daisuke ; Yamanaka, Kazuki
Author_Institution :
Graduate Sch. of Eng. Sci., Osaka Univ., Japan
Volume :
3
fYear :
2005
fDate :
10-12 Oct. 2005
Firstpage :
2781
Abstract :
In this paper, it is proposed to cluster decision classes before applying a rule induction method. The similarity between decision classes is defined and an agglomerative hierarchical clustering method is applied. At each branch of the obtained dendrogram, LEM2, one of frequently used rule induction algorithm, is applied to induce decision rules inferring clusters. In such a way, a set of decision rules classifying objects into decision classes is obtained. The performance of the proposed method is compared with the direct application of LEM2 to each decision class by a numerical experiment.
Keywords :
data mining; decision theory; inference mechanisms; pattern classification; pattern clustering; LEM2 algorithm; agglomerative hierarchical clustering method; clustering decision classes; decision rules; rule induction method; Clustering algorithms; Clustering methods; Data analysis; Humans; Information analysis; Rough sets; Rough set; clustering; rule induction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2005 IEEE International Conference on
Print_ISBN :
0-7803-9298-1
Type :
conf
DOI :
10.1109/ICSMC.2005.1571571
Filename :
1571571
Link To Document :
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