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Real-time fuzzy classification problem: application of optimal fuzzy linear regression with support vector machine

Ramli, Azizul Azhar and Witold Pedrycz, Witold Pedrycz and Junzo Watada, Junzo Watada (2011) Real-time fuzzy classification problem: application of optimal fuzzy linear regression with support vector machine. In: 3rd IEEE International Conference on Machine Learning and Computing (ICMLC 2011) , 26-28 February 2011 , Singapore.

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Abstract

Soft computing helps model and classifier exploit tolerance for imprecision and uncertainly. In this paper, we proposed a hybrid approach to combine fuzzy regression analysis with support vector machine (SVMs). The proposed approach is suitable for the real-time treatment of classification problems. For the developed hybrid structure of the fuzzy classifier, we show simulation results the highlight two main advantages, namely the decrease of required complexity. We show that the proposed intelligent data analysis (IDA) becomes an efficient way to analyse data in real-time environment, specifically in fuzzy classification problems.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: convex-hull; fuzzy classification; modified fuzzy linear regression; intelligent data analysis; support vector machine
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 07 Feb 2013 10:17
Last Modified: 21 Jan 2015 07:14
URI: http://eprints.uthm.edu.my/id/eprint/2977
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