A novel and efficient neuro-fuzzy classifier for medical diagnosis

Chin-Ming Hong, Chih Ming Chen, Syuan-Yi Chen, Chao Yen Huang

    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

    This study attempts to propose a novel neuro-fuzzy network which can efficiently reason fuzzy rules based on training data to solve the medical diagnosis problems. First, this study proposes a refined K-means clustering algorithm and a gradient-based learning rules to logically determine and adaptively tuned the fuzzy membership functions for the employed neuro-fuzzy network. In the meanwhile, this study also presents a feature reduction scheme based on the grey-relational analysis to simplify the fuzzy rules obtained from the employed neuro-fuzzy network. Experimental results indicated that the proposed neuro-fuzzy network with feature reduction can discover very simplified and easily interpretable fuzzy rules to support medical diagnosis.

    原文英語
    主出版物標題International Joint Conference on Neural Networks 2006, IJCNN '06
    頁面735-741
    頁數7
    出版狀態已發佈 - 2006 十二月 1
    事件International Joint Conference on Neural Networks 2006, IJCNN '06 - Vancouver, BC, 加拿大
    持續時間: 2006 七月 162006 七月 21

    出版系列

    名字IEEE International Conference on Neural Networks - Conference Proceedings
    ISSN(列印)1098-7576

    其他

    其他International Joint Conference on Neural Networks 2006, IJCNN '06
    國家加拿大
    城市Vancouver, BC
    期間06/7/1606/7/21

    ASJC Scopus subject areas

    • Software

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