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
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