Real-time fuzzy classification problem: application of optimal fuzzy linear regression with support vector machine
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....
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/2977/ |
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| Summary: | 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. |
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