Fuzzy support vector machines with the uncertainty of parameter C

Author:

Hsu Che-Chang,Han Ming-Feng,Chang Shih-Hsing,Chung Hung-Yuan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference13 articles.

1. Breiman, L. (1996). Bias, variance and arcing classifiers, technical report 460. CA: Statistics Department, University of California.

2. The elements of statistical learning: Data mining, inference and prediction;Hastie,2001

3. Training algorithms for fuzzy support vector machine with noisy data;Lin;Pattern Recognition Letters archive,1999

4. Tax, D. M. J., & Duin, R. P. W. (2005). Characterizing one-class datasets. In Proceedings of the 16th annual symposium of the pattern recognition association of South Africa (pp. 21–26).

5. Murphy, P. M. (1995). UCI-benchmark repository of artificial and real data sets. http://www.ics.uci.edu/~mlearn, CA: University of California Irvine.

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