Visualizing discovered rule sets with visual graphs based on compressed entropy density

Einoshin Suzuki, Hiroki Ishihara

研究成果: 著書/レポートタイプへの貢献会議での発言

1 引用 (Scopus)

抜粋

This paper presents a post-processing algorithm of rule discovery for augmenting the readability of a discovered rule set. Rule discovery, in spite of its usefulness as a fundamental data-mining technique, outputs a huge number of rules. Since usefulness of a discovered rule is judged by human inspection, augmenting the readability of a discovered rule set is an important issue. We formalize this problem as a transformation of a rule set into a tree structure called a visual graph. A novel information-based criterion which represents compressed entropy of a data set per description length of the graph is employed in order to evaluate the readability quantitatively. Experiments with an agricultural data set in cooperation with domain experts confirmed the effectiveness of our method in terms of readability and validness.

元の言語英語
ホスト出版物のタイトルNew Directions in Rough Sets, Data Mining, and Granular-Soft Computing - 7th International Workshop, RSFDGrC 1999, Proceedings
編集者Setsuo Ohsuga, Ning Zhong, Andrzej Skowron
出版者Springer Verlag
ページ414-423
ページ数10
ISBN(印刷物)3540666451, 9783540666455
DOI
出版物ステータス出版済み - 1 1 1999
外部発表Yes
イベント7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC 1999 - Yamaguchi, 日本
継続期間: 11 9 199911 11 1999

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)
1711
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

その他

その他7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC 1999
日本
Yamaguchi
期間11/9/9911/11/99

    フィンガープリント

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

これを引用

Suzuki, E., & Ishihara, H. (1999). Visualizing discovered rule sets with visual graphs based on compressed entropy density. : S. Ohsuga, N. Zhong, & A. Skowron (版), New Directions in Rough Sets, Data Mining, and Granular-Soft Computing - 7th International Workshop, RSFDGrC 1999, Proceedings (pp. 414-423). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 1711). Springer Verlag. https://doi.org/10.1007/978-3-540-48061-7_50