Article ID Journal Published Year Pages File Type
532789 Pattern Recognition 2008 10 Pages PDF
Abstract

In many systems, such as fuzzy neural network, we often adopt the language labels (such as large, medium, small, etc.) to split the original feature into several fuzzy features. In order to reduce the computation complexity of the system after the fuzzification of features, the optimal fuzzy feature subset should be selected. In this paper, we propose a new heuristic algorithm, where the criterion is based on min–max learning rule and fuzzy extension matrix is designed as the search strategy. The algorithm is proved in theory and has shown its high performance over several real-world benchmark data sets.

Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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