| 一种局部概率引导的优化K-means++算法 |
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| 引用本文： | 王海燕,崔文超,许佩迪,李闯.一种局部概率引导的优化K-means++算法[J].吉林大学学报(理学版),2019,57(6):1431-1436. |
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| 作者姓名： | 王海燕 崔文超 许佩迪 李闯 |
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| 作者单位： | 长春大学计算机科学技术学院,长春130022;吉林大学理论化学研究所,长春130021;吉林师范大学计算机学院,吉林四平,136000 |
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| 基金项目： | 国家自然科学基金;吉林省教育厅十三五科学规划项目;吉林师范大学博士启动基金 |
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| 摘 要： | 针对K-means++算法选取初始聚类中心计算误差平方和时, 实验次数对误差平方影响不准确的问题， 提出一种PK-means++算法. 结果表明, 该算法在进行分散数据聚类时, 在同一K值情形下, 聚类后的误差平方和较原K-means++算法更稳定, 从而更好地保证了随机实验取值的稳定性.
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| 关 键 词： | 聚类分析 K-means++算法 概率 误差平方和 |
| 收稿时间： | 2019-04-28 |
An Optimized K-means++ Algorithm Guided by Local Probability |
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| WANG Haiyan,CUI Wenchao,XU Peidi,LI Chuang.An Optimized K-means++ Algorithm Guided by Local Probability[J].Journal of Jilin University: Sci Ed,2019,57(6):1431-1436. |
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| Authors: | WANG Haiyan CUI Wenchao XU Peidi LI Chuang |
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| Institution: | 1. College of Computer Science and Technology, Changchun University, Changchun 130022, China;2. Institute of Theoretical Chemistry, Jilin University, Changchun 130021, China; 3. College of Computer, Jilin Normal University, Siping 136000, Jilin Province, China
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| Abstract: | Aiming at the problem that the number of experiment had an inaccurate effect on the square of errors when the K-
means++ algorithm was used to select the initial clustering center to calculate the sum squared error, we proposed a PK-means++ algorithm. The results show that the sum squared error after clustering is more stable than the original K-means++ algorithm under the same K-value when the algorithm clusters the scattered data, so the stability of random experiment value is better guaranteed. |
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| Keywords: | clustering analysis K-means++ algorithm probability sum squared error |
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