一种增量式MinMax k-Means聚类算法  

An Incremental MinMax k-Means Clustering Algorithm

作　　者：胡雅婷[1] 陈营华 宝音巴特 曲福恒[3] 李卓识[1] HU Yating;CHEN Yinghua;BAOYIN Bate;QU Fuheng;LI Zhuoshi(School of Information and Technology,Jilin Agriculture University,Changchun 130118,China;Jilin Science and Technology Works Service Center,Changchun 130021,China;School of Computer Science and Technology,Changchun University of Science and Technology,Changchun 130022,China)

机构地区：[1]吉林农业大学信息技术学院,长春130118 [2]吉林省科学技术工作者服务中心,长春130021 [3]长春理工大学计算机科学技术学院,长春130022

出　　处：《吉林大学学报（理学版）》2021年第5期1205-1211,共7页Journal of Jilin University:Science Edition

基　　金：国家自然科学基金(批准号:41671397);吉林省科技发展计划项目(批准号:20191001008XH);吉林省生态环境厅科技项目(批准号:2020-18);吉林省教育厅科学技术研究项目(批准号:JJKH20190922KJ;JJKH20210331KJ);吉林省发展与改革委员会预算内基本建设资金计划项目(批准号:2020C037-7).

摘　　要：针对MinMax k-means算法易产生空解、收敛速度慢和计算效率低的问题,提出一种增量式MinMax k-means聚类算法.该算法从给定的初始聚类个数开始,以固定步长递增式产生新的聚类中心,采用基于数据均衡的快速分裂方法产生增量聚类中心,从而避免了传统增量聚类中心选择中遍历数据、k-means聚类算法运行次数过多导致的大计算量问题.与MinMax k-means及相关算法的对比实验结果表明,该算法在计算效率和求解精度上均优于对比算法,有效改善了MinMax k-means聚类对初始化中心敏感和易产生空解的问题.Aiming at the problem that MinMax k-means algorithm was easy to generate empty solutions,slow convergence speed and low computational efficiency,we proposed an incremental MinMax k-means clustering algorithm.The algorithm started from a given initial clustering number,and generated new cluster centers by increasing a fixed step length.The fast dividing method based on data balance was used to generate incremental cluster centers,so as to avoid the large amount of calculation problem caused by traversing data and too many running times of k-means clustering algorithm in traditional incremental clustering center selection.Compared with MinMax k-means and related algorithms,the experimental results show that the algorithm is superior to the comparison algorithm in calculation efficiency and accuracy,and effectively improves the sensitivity of MinMax k-means clustering to initialization center and easy to generate empty solutions.

关 键 词：K均值聚类 增量式聚类 初始化 聚类中心 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]