LEM2-based rule induction via clustering decision classes

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...

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Bibliographic Details
Main Authors: Inuiguchi, M., Tsurumi, M., Fukuda, D., Yamanaka, K.
Format: Conference Proceeding
Language:English
Subjects:
clustering
Clustering algorithms
Clustering methods
Data analysis
Humans
Information analysis
Rough set
Rough sets
rule induction
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Summary: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.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.2005.1571571