Research on Improved Partition Clustering Method Based on K-Means Algorithm

摘要：

　　Partition-based clustering algorithm is an optimization search algorithm based on mountain climbing,which is simple,fast and effective.The criterion of dividing is that the data objects in the same cluster are as similar as possible,and the data objects in different clusters are as different as possible.The k-means algorithm is a classical algorithm to solve the clustering problem.The most important feature of the algorithm is that it adopts a two-stage repeated loop structure.The condition of the end of the algorithm is that no data elements are redistributed.The paper presents improved partition clustering method based on K-means algorithm.

关键词： K-Means Algorithm Partition Clustering Mountain Climbing Repeated Loop Structure V Data Mining

作者: Qing Tan Wuchao Zhao

作者单位: Luoyang Normal University,Henan Luoyang,471934,China

会议类型: 国际会议

会议名称: 2019年第二届智能系统研究与机电工程国际会议(ISRME 2019) 2019 2nd International Conference on Intelligent Systems Research and Mechatronics Engineering

会议地点: 太原

会议语种:英文

页码: 27-31

在线出版日期: 2019-06-29（万方平台首次上网日期，不代表论文的发表时间）