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)


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.

主出版物標題Proceedings of the Asian Fuzzy Systems Symposium
編輯Y.Y. Chen, K. Hirota, J.Y. Yen
出版狀態已發佈 - 1996
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Proceedings of the 1996 Asian Fuzzy Systems Symposium
城市Kenting, Taiwan

ASJC Scopus subject areas

  • Engineering(all)

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