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ID 25635
本文ファイル
著者
Yamaguchi, Takashi
Ichimura, Takumi
Mackin, Kenneth J.
NDC
技術・工学
抄録(英)
It is known that the classification of medical data is difficult problem because the medical data has ambiguous information or missing data. As a result, the classification method that can handle ambiguous information or missing data is necessity. In this paper we proposed an adaptive tree structure clustering method in order to clarify clustering result of selforganizing feature maps. For the evaluating effectiveness of proposed clustering method for the data set with ambiguous information, we applied an adaptive tree structured clustering method for classification of coronary heart disease database. Through the computer simulation we showed that the proposed clustering method was effective for the ambiguous data set.
掲載誌名
Fourth International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2008
開始ページ
139
終了ページ
144
出版年月日
2008-12
出版者
IEEE SMC Hiroshima Chapter
ISSN
1883-3977
言語
英語
NII資源タイプ
会議発表論文
広大資料タイプ
会議発表論文
DCMIタイプ
text
フォーマット
application/pdf
著者版フラグ
publisher
権利情報
(c) Copyright by IEEE SMC Hiroshima Chapter.
部局名
工学研究科