Robustified distance based fuzzy membership function for support vector machine classification

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MOHAMMADI M.; SARMAD M.

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Journal Paper

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Journal: Iranian Journal of Fuzzy Systems Year:2019 | Volume:16 | Issue:6 Page(s): 191-204

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Information Journal Paper

Title

Robustified distance based fuzzy membership function for support vector machine classification

Author(s)

MOHAMMADI M. | SARMAD M. | Issue Writer Certificate

Keywords

Support vector machineQ2

Noise/outlierQ2

Robust statisticsQ2

Fuzzy membership functionQ2

Minimum covariance determinant estimatorQ2

Orthogonalised Gnanadesikan Kettenring estimatorQ2

Abstract

Fuzzification of Support vector machine has been utilized to deal with outlier and noise problem. This importance is achieved, by the means of Fuzzy membership function, which is generally built based on the distance of the points to the class centroid. The focus of this research is twofold. Firstly, by taking the advantage of Robust statistics in the fuzzy SVM, more emphasis on reducing the impact of outliers on the generalizability of SVM has been placed. Moreover, the variety of membership function for the elliptical data has been designated, based on the classic and robust Mahalanobis distance. Minimum covariance determinant and Orthogonalised Gnanadesikan Kettenring estimators are employed in the structure of the robust– fuzzy SVM. By implementing the new membership function, the disadvantages of the traditional Fuzzy membership function has been rectified. Simulated and real benchmarking data set confirm the effectiveness of the proposed methods. Compared with the traditional SVM and fuzzy SVM, these methods give a better performance on reducing the effects of outliers and significantly improves the classification accuracy and generalization.

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APA: Copy

MOHAMMADI, M., & SARMAD, M.. (2019). Robustified distance based fuzzy membership function for support vector machine classification. IRANIAN JOURNAL OF FUZZY SYSTEMS, 16(6 ), 191-204. SID. https://sid.ir/paper/404543/en

Vancouver: Copy

MOHAMMADI M., SARMAD M.. Robustified distance based fuzzy membership function for support vector machine classification. IRANIAN JOURNAL OF FUZZY SYSTEMS[Internet]. 2019;16(6 ):191-204. Available from: https://sid.ir/paper/404543/en

IEEE: Copy

M. MOHAMMADI, and M. SARMAD, “Robustified distance based fuzzy membership function for support vector machine classification,” IRANIAN JOURNAL OF FUZZY SYSTEMS, vol. 16, no. 6 , pp. 191–204, 2019, [Online]. Available: https://sid.ir/paper/404543/en

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