Multi-strategy instance selection in mining chronic hepatitis data

Authors:
Masatoshi Jumi;Einoshin Suzuki;Muneaki Ohshima;Ning Zhong;Hideto Yokoi;Katsuhiko Takabayashi
Affiliations:
Electrical and Computer Engineering, Yokohama National University, Japan;Electrical and Computer Engineering, Yokohama National University, Japan;Faculty of Engineering, Maebashi Institute of Technology, Japan;Faculty of Engineering, Maebashi Institute of Technology, Japan;Department of Medical Informatics, Kagawa University Hospital, Japan;Division of Medical Informatics, Chiba University Hospital, Japan
Venue:
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
Year:
2005

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Abstract

In this paper, we propose a method which splits examples into typical and exceptional by mainly assuming that an example represents a case. The split is based on our previously developed data mining methods and a novel likelihood-based criterion. Such a split represents a highly intellectual activity thus the method is assumed to support the users, who are typically medical experts. Experiments with the chronic hepatitis data showed that our proposed method is effective and promising from various viewpoints.