OSDM: Optimized Shape Distribution Method

Ashkan Sami, Ryoichi Nagatomi, Makoto Takahashi, Takeshi Tokuyama

研究成果: Conference contribution

抄録

Comprehensibility is vital in results of medical data mining systems since doctors simply require it. Another important issue specific to some data sets, like Fitness, is their uniform distribution due to tile analysis that was performed on them. In this paper, we propose a novel data mining tool named OSDM (Optimized Shape Distribution Method) to give a comprehensive view of correlations of attributes in cases of uneven frequency distribution among different values of symptoms. We apply OSDM to explore the relationship of the Fitness data and symptoms in medical test dataset for which popular data mining methods fail to give an appropriate output to help doctors decisions. In our experiment, OSDM found several useful relationships.

本文言語English
ホスト出版物のタイトルAdvanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings
編集者Xue Li, Osmar R. Zaïane, Zhanhuai Li
出版社Springer Verlag
ページ1057-1064
ページ数8
ISBN(印刷版)3540370250, 9783540370253
DOI
出版ステータスPublished - 2006
イベント2nd International Conference on Advanced Data Mining and Applications, ADMA 2006 - Xi'an, China
継続期間: 2006 8 142006 8 16

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4093 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other2nd International Conference on Advanced Data Mining and Applications, ADMA 2006
国/地域China
CityXi'an
Period06/8/1406/8/16

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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