Integration of fuzzy classifiers with decision trees

I. J. Chiang, J. Y. Hsu

研究成果: 書貢獻/報告類型會議貢獻

10 引文 斯高帕斯(Scopus)

摘要

It is often difficult to make accurate predictions given uncertain and noisy data for classification. Unfortunately, most real-world problems have to deal with such imperfect data. This paper presents a new model for fuzzy classification by integrating fuzzy classifiers with decision trees. In this approach, a fuzzy classification tree is constructed from the training data set. Instead of defining a specific class for a given instance, the proposed fuzzy classification scheme computes its degree of possibility for each class. The performance of the system is evaluated by empirically compared with a standard decision tree classifier C4.5 on several benchmark data sets the UCI machine learning repository.

原文英語
主出版物標題Proceedings of the Asian Fuzzy Systems Symposium
編輯Y.Y. Chen, K. Hirota, J.Y. Yen
發行者IEEE
頁面266-271
頁數6
出版狀態已發佈 - 1996
對外發佈Yes
事件Proceedings of the 1996 Asian Fuzzy Systems Symposium - Kenting, Taiwan
持續時間: 十二月 11 1996十二月 14 1996

其他

其他Proceedings of the 1996 Asian Fuzzy Systems Symposium
城市Kenting, Taiwan
期間12/11/9612/14/96

ASJC Scopus subject areas

  • Engineering(all)

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  • 引用此

    Chiang, I. J., & Hsu, J. Y. (1996). Integration of fuzzy classifiers with decision trees. 於 Y. Y. Chen, K. Hirota, & J. Y. Yen (編輯), Proceedings of the Asian Fuzzy Systems Symposium (頁 266-271). IEEE.