| 一种基于简单遗传算法的K-Means改进算法 |
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| 引用本文： | 尹鹏飞,张晓丹. 一种基于简单遗传算法的K-Means改进算法[J]. 吉首大学学报(自然科学版), 2009, 30(6): 43-45 |
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| 作者姓名： | 尹鹏飞 张晓丹 |
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| 作者单位： | 吉首大学教务处,湖南,吉首,416000;吉首大学数计学院,湖南,吉首,416000 |
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| 摘 要： | 针对k-means算法对初始值敏感、易陷入局部极小值等缺点,结合遗传算法的思想,提出了一种基于遗传算法和k-means算法的混合聚类方法,为了测试该聚类算法的性能,用k-means 算法和改进的算法进行了1组实验,并对2种算法的聚类结果进行比较,实验结果表明算法能够有效地解决聚类问题.
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| 关 键 词： | 数据挖掘 聚类分析 遗传算法K-means算法 |
Improved K-Means Algorithm Based on a Simple Genetic Algorithm |
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| YIN Peng-fei,ZHANG Xiao-dan. Improved K-Means Algorithm Based on a Simple Genetic Algorithm[J]. Journal of Jishou University(Natural Science Edition), 2009, 30(6): 43-45 |
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| Authors: | YIN Peng-fei ZHANG Xiao-dan |
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| Affiliation: | (1.Office of Education Administration,Jishou University,Jishou 416000,Hunan China;2.College of Mathematics and Computer Science,Jishou University,Jishou 416000,Hunan China) |
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| Abstract: | K-means algorithm is sensitive to initial value,easy to fall into local minimum value.In response to these shortcomings,the idea of genetic algorithm is proposed based on genetic algorithm and k-means algorithm for hybrid clustering method.In order to test the performance of clustering algorithm,a set of experiments are conducted by using k-means algorithm and the improved algorithm,and the clustering results by the two algorithms are compared.It is showed that the clustering algorithm can effectively solve the clustering problem. |
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| Keywords: | data mining cluster analysis genetic algorithm k-means algorithm |
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