| 基于免疫聚类算法的离群数据挖掘 |
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| 引用本文： | 朱志勇,林睦纲.基于免疫聚类算法的离群数据挖掘[J].系统工程,2009,27(3). |
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| 作者姓名： | 朱志勇 林睦纲 |
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| 作者单位： | 朱志勇,ZHU Zhi-yong(长沙学院,计算机科学与技术系,湖南,长沙,410003);林睦纲,LIN Mu-gang(衡阳师范学院,计算机科学系,湖南,衡阳,421008)
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| 基金项目： | 湖南省教育厅资助项目，长沙学院资助科研项目 |
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| 摘 要： | 离群数据挖掘是数据挖掘研究的重要内容,在实际生活中获得广泛应用.论文结合了免疫算法全局搜索的优点和K-均值方法局部收敛速度快的特点,提出了一种基于免疫聚类算法的离群数据挖掘方法,有效地克服了传统聚类方法对初始化敏感、容易陷入局部最优等缺点,使聚类结果能够快速收敛到全局最优,有效地检测离群数据.实验结果表明,该方法实用有效的.
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| 关 键 词： | 离群数据挖掘 数据挖掘 免疫算法 K-均值聚类 |
Outlier Data Mining Based on Immune Clustering Algorithm |
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| ZHU Zhi-yong,LIN Mu-gang.Outlier Data Mining Based on Immune Clustering Algorithm[J].Systems Engineering,2009,27(3). |
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| Authors: | ZHU Zhi-yong LIN Mu-gang |
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| Institution: | ZHU Zhi-yong1,LIN Mu-gang2(1. Department of Computer Science and Technology,Changsha University,Changsha 41003 China,2.Department of Computer Science,Hengyang Normal University,Hengyang 421008,China) |
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| Abstract: | Outlier mining is an important issue in data mining and it is applied widely in practice.By combining the advantages global searching of the immune algorithm with fast local convergence rate of the Kmeans method,a new outlier mining method based on Immune algorithm and clustering is presented.The method can be neither sensitive to initialization nor be easy to get trapped into local optima.Not only can the result of clustering quickly converge to the global optimization,but also it can detect the outliers i... |
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| Keywords: | Outlier Mining Data Mining Immune Algorithm K-means Cluster |
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