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FUZZY PARTITIONING OF FEATURE SPACE FOR PATTERN CLASSIFICATION BASED ON SUPERVISED C1USTERING

FUZZY PARTITIONING OF FEATURE SPACE FOR PATTERN CLASSIFICATION BASED ON SUPERVISED C1USTERING
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摘要 The choice of a fuzzy partitioning is crucial to the performance of a fuzzy system based on if-then rules. However, most of the existing methods are complicated or lead ,o too many subspaces, which is unfit for the applications of pattern classification. A simple but effective clustering approach is proposed in this paper, which obtains a set of compact subspaces and is applicable for classification problems with higher dimensional feature. Its effectiveness is demonstrated by the experimental results. The choice of a fuzzy partitioning is crucial to the performance of a fuzzy system based on if-then rules. However, most of the existing methods are complicated or lead ,o too many subspaces, which is unfit for the applications of pattern classification. A simple but effective clustering approach is proposed in this paper, which obtains a set of compact subspaces and is applicable for classification problems with higher dimensional feature. Its effectiveness is demonstrated by the experimental results.
出处 《Journal of Electronics(China)》 2000年第2期170-177,共8页 电子科学学刊(英文版)
关键词 PATTERN CLASSIFICATION FUZZY if-then RULES FUZZY CLUSTERING FUZZY partitioning Pattern classification Fuzzy if-then rules Fuzzy clustering Fuzzy partitioning
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