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This paper reviews the advances of type-2 fuzzy sets for pattern classification. The recent success of type-2 fuzzy sets has been largely attributed to their three-dimensional membership functions to handle more uncertainties in real-world problems. In pattern classification, both feature and hypothesis spaces have uncertainties, which motivate us of integrating type-2 fuzzy sets with traditional classifiers to achieve a better performance in terms of robustness, generalization ability, ordoi:10.1109/foci.2007.372168 dblp:conf/foci/ZengL07 fatcat:jchjr6fgtbb2pc3hqu33ijqexi