| 基于最近邻原则的半监督聚类算法 |
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| 引用本文： | 计华,张化祥,孙晓燕.基于最近邻原则的半监督聚类算法[J].计算机工程与设计,2011,32(7):2455-2458. |
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| 作者姓名： | 计华 张化祥 孙晓燕 |
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| 作者单位： | 山东师范大学计算机系,山东济南,250014 |
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| 基金项目： | 山东省科技研究计划基金项目(2007ZZ17、2008GG10001015、2008B0026、ZR2010FM021、2010G0020115); 山东省教育厅科研基金项目(J09LG02) |
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| 摘 要： | 基于最近邻原则的半监督聚类算法是以基于最近邻的聚类中心求解算法为基础的。在基于最近邻的聚类中心求解算法中,用相似度矩阵记录数据点间的相似程度,由目标函数最小值求得聚类的类中心点。在基于最近邻原则的半监督聚类算法中,根据约束信息来调整相似度矩阵G,数据点间相似度的变化引起了数据点间加权欧式距离的变化,由此更新加权欧式距离矩阵M,最后执行聚类中心求解算法完成聚类。大量实验结果表明,该算法能获得较好的聚类结果。
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| 关 键 词： | 最近邻原则 加权欧式距离矩阵 半监督聚类 类中心点 约束信息 |
Semi-supervised clustering algorithm based on nearest-neighbor |
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| JI Hua,ZHANG Hua-xiang,SUN Xiao-yan.Semi-supervised clustering algorithm based on nearest-neighbor[J].Computer Engineering and Design,2011,32(7):2455-2458. |
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| Authors: | JI Hua ZHANG Hua-xiang SUN Xiao-yan |
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| Affiliation: | JI Hua,ZHANG Hua-xiang,SUN Xiao-yan(Department of Computer Science,Shandong Normal University,Jinan 250014,China) |
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| Abstract: | At present,semi-supervised clustering is studied extensively in machine learning,because it is demonstrated that unsupervised clustering can be significantly improved by using supervision constraints.The nearest-neighbor based semi-supervised clustering(NNBSSC) algorithm is proposed for enhancing clustering quality by employing such supervision.At first,a nearest-neighbor based clustering centers solving algorithm is introduced,in which all the distance between two data points are presented in the similarit... |
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| Keywords: | nearest-neighbor rule weighted Euclidean distance matrix semi-supervised clustering class center points constraint information |
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