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Genetic algorithm-based clustering technique

机译:基于遗传算法的聚类技术

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摘要

A genetic algorithm-based clustering technique, called GA-clustering, is proposed in this article. The searching capability of genetic algorithms is exploited in order to search for appropriate cluster centres in the feature space such that a similarity metric of the resulting clusters is optimized. The chromosomes, which are represented as strings of real numbers, encode the centres of a fixed number of clusters. The superiority of the GA-clustering algorithm over the commonly used K-means algorithm is extensively demonstrated for four artificial and three real-life data sets. (C) 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved. [References: 32]
机译:本文提出了一种基于遗传算法的聚类技术,称为GA聚类。利用遗传算法的搜索能力以便在特征空间中搜索适当的聚类中心,从而优化所得聚类的相似性度量。代表实数字符串的染色体编码固定数目的簇的中心。 GA聚类算法相对于常用K均值算法的优越性已在四个人工和三个真实数据集上得到了充分证明。 (C)2000模式识别学会。由Elsevier Science Ltd.出版。保留所有权利。 [参考:32]

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