| 基于孤立点和初始质心选择的κ-均值改进算法 |
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| 引用本文： | 顾洪博,张继怀.基于孤立点和初始质心选择的κ-均值改进算法[J].长江大学学报,2009(1):60-62. |
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| 作者姓名： | 顾洪博 张继怀 |
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| 作者单位： | [1]大庆石油学院计算机与信息技术学院,黑龙江大庆163318 [2]大庆市让胡路区政府,黑龙江大庆163712 |
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| 基金项目： | 黑龙江省教育厅科学技术研究项目(11521008); 黑龙江省自然科学基金资助项目(F200603) |
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| 摘 要： | 介绍了在聚类中广泛应用的经典κ-均值算法，针对其随机选择初始质心和易受孤立点的影响的不足，给出了一种改进的κ-均值算法。首先使用距离法移除孤立点，然后采用邻近吸收法对初始质心的选择上进行了改进，并做了改进前后的对比试验。试验结果表明，改进后的算法比较稳定、准确，受孤立点和随机选择质心的影响也有所降低。
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| 关 键 词： | κ-均值算法 孤立点 初始质心 距离 |
An Improved k-means Algorithm Based on Outliers and Original Clustering Center |
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| GU Hong-boZHANG Ji-huai.An Improved k-means Algorithm Based on Outliers and Original Clustering Center[J].Journal of Yangtze University,2009(1):60-62. |
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| Authors: | GU Hong-boZHANG Ji-huai |
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| Institution: | GU Hong-bo(Daqing Petroleum Institute,Daqing 163318)ZHANG Ji-huai(Daqing City Ranghulu District Government,Daqing 163712) |
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| Abstract: | The classic algorithm of k-means was discussed,that was one of the most widespread methods in clustering,including both strongpoints and shortages.Not only is it sensitive to the original clustering center,but also it may be affected by the outliers.Given these shortages,an improved algorithm is discussed,which makes improvements in outliers and selection of original clustering center.The outlier detection is based on the distance method.To select original clustering center is assimilated based on the neare... |
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| Keywords: | algorithm of k-means outliers original clustering center distance |
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