Fuzzy Cost Support Vector Regression

Authors: Hadi Sadoghi Yazdi, Tahereh Royani, Mehri Sadoghi Yazdi, Sohrab Effati

Abstract:

In this paper, a new version of support vector regression (SVR) is presented namely Fuzzy Cost SVR (FCSVR). Individual property of the FCSVR is operation over fuzzy data whereas fuzzy cost (fuzzy margin and fuzzy penalty) are maximized. This idea admits to have uncertainty in the penalty and margin terms jointly. Robustness against noise is shown in the experimental results as a property of the proposed method and superiority relative conventional SVR.

Keywords: Support vector regression, Fuzzy input, Fuzzy cost.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1081820

References:

[1] C-f. Lin, S-d. Wang, "Fuzzy Support Vector Machine," IEEE Trans. on Neural Networks, 2002, vol. 13, no. 2, pp. 464-471, Mar. 2002.
[2] C-f. Lin, S-d. Wang "Training Algorithms for Fuzzy Support Vector Machines with Noisy Data," Pattern Recognition Letters, vol.25, pp. 1647-1656, 2004.
[3] D.H. Hong, C. Hwang, "Support vector fuzzy regression machines," Fuzzy Sets and Systems 138, pp.271-281, 2003.
[4] A-B. Ji, J-H. Pang, S-H. Li, J-P. Sun, "Support Vectro Machine for Classification Based on Fuzzy Training Data," Proceedings of the Fifth Int. Conf. on Machine Learning and Cybernetics, Dalian, pp.1609-1614, 13-16 August 2006.
[5] H.Sadoghi Yazdi, S. Effati, Z. Saberi, "The Probabilistic Constraints in the Support Vector Machine," Applied Mathematics and Computation, vol.194, no.2, p.467-479, Dec 2007 .
[6] Y-H. Liu, and Y-T. Chen, "Face Recognition Using Total Margin-Based Adaptive Fuzzy Support Vector Machines," IEEE Trans. on Neural Networks, vol. 18, no.1, pp.178-192, Jan. 2007.
[7] L. Chu, and C. Wu, "A Fuzzy Support Vector Machine Based on Geometric Model," Proceedings of the fifth World Congress on Intelligent Control and Automation, Hangzhou, P.R. China, pp.1843- 1846,June 15-19,2004.
[8] Y. Wang, S. Wang, and K. K. Lai, "A New Fuzzy Support Vector Machine to Evaluate Credit Risk," IEEE Trans. on Fuzzy Systems, vol.13 no.6, pp.820-831, Dec. 2005.
[9] Jayadeva, R. Khemchandani, S. andra, "Fuzzy Linear Proximal Support Vector Machines for Multi-Category Data Classification," Neurocomputing, vol.67, pp.426-435, 2005.
[10] T-Y. Wang, H-M. Chiang, "Fuzzy Support Vector Machine for Multi- Class Text Categorization," Information Processing and Management, vol.43, pp.914-929, 2007.