システム制御情報学会論文誌
Online ISSN : 2185-811X
Print ISSN : 1342-5668
ISSN-L : 1342-5668
楕円領域を持つファジィクラシファイアのロバスト化
江口 卓志玉置 久阿部 重夫
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2000 年 13 巻 9 号 p. 433-440

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In this paper, we discuss a robust training method for a fuzzy classifier with ellipsoidal regions. First, we define a fuzzy rule for each class. Next, we determine the weight for each training datum Dy the two-stage method in order to suppress the effect of outliers. Then, using these weights, we calculate the center and covariance matrix of the ellipsoidal region for each class and tune the Fuzzy rules. After tuning, to further improve generalization ability, we tune fuzzy rules between two classes using the training data in the class boundary. We demonstrate the effectiveness of our method using four benchmark data sets.

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