会议专题

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

  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.

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

Qing Tan Wuchao Zhao

Luoyang Normal University,Henan Luoyang,471934,China

国际会议

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

太原

英文

27-31

2019-06-29(万方平台首次上网日期,不代表论文的发表时间)