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Mining Representative Subset Based on Fuzzy Clustering 被引量:1
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作者 ZHOU Hongfang FENG Boqin LU Lintao 《Wuhan University Journal of Natural Sciences》 CAS 2007年第5期799-803,共5页
Two new concepts-fuzzy mutuality and average fuzzy entropy are presented. Then based on these concepts, a new algorithm-RSMA (representative subset mining algorithm) is proposed, which can abstract representative su... Two new concepts-fuzzy mutuality and average fuzzy entropy are presented. Then based on these concepts, a new algorithm-RSMA (representative subset mining algorithm) is proposed, which can abstract representative subset from massive data. To accelerate the speed of producing representative subset, an improved algorithm-ARSMA(accelerated representative subset mining algorithm) is advanced, which adopt combining putting forward with backward strategies. In this way, the performance of the algorithm is improved. Finally we make experiments on real datasets and evaluate the representative subset. The experiment shows that ARSMA algorithm is more excellent than RandomPick algorithm either on effectiveness or efficiency. 展开更多
关键词 representative subset fuzzy mutuality fuzzy entropy COVERAGE REDUNDANCY
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