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Fuzzy set theory and fuzzy logic provide tools for handling uncertainties in data mining tasks. To design a fuzzy rule-based classification system (fuzzy classifier) with good generalization ability in a high dimensional feature space has been an active research topic for a long time. As a powerful machine learning approach for data mining and pattern recognition problems, support vector machine (SVM) is known to have good generalization ability. More importantly, an SVM can work very well on a high (or even infinite) dimensional feature space. This chapter presents a survey of the connection between fuzzy classifiers and kernel machines. A significant portion of the chapter is built upon material from articles we have written, in particular (Chen and Wang, 2003a, Chen and Wang, 2003b).

Keywords

Support Vector Machine Membership Function Fuzzy System Fuzzy Rule Reference Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Yixin Chen
    • 1
  1. 1.Dept. of Computer and Information ScienceThe University of MississippiUSA

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