K-means Initial Clustering Center Optimal Algorithm Based on Estimating Density and Refining Initial

被引：0
|
作者：
Ai, Hui [1 ]
Li, Wei [2 ]
机构：
[1] Northwestern Polytech Univ, Coll Automat Control, Xian, Shaanxi, Peoples R China
[2] Taiyuan Univ Technol, Taiyuan, Shanxi, Peoples R China
来源：
2012 6TH INTERNATIONAL CONFERENCE ON NEW TRENDS IN INFORMATION SCIENCE, SERVICE SCIENCE AND DATA MINING (ISSDM2012) | 2012年
关键词：
clustering initialization; estimating density algorithm; refining initial algorithm; k-means;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The performance of K-means clustering algorithm strongly depends on the initial parameters. Based on the segmenting algorithm of density estimation and large scale data group segmenting algorithm of the initial value limitation, a new algorithm for initializing the cluster center is presented. The idea of segmenting base on density is combined with the idea of sampling and the new idea is presented. The accuracy of sampling is improved by averagely segmenting every dimension of the database. The speediness of the refining initial algorithm ensures the new algorithm has superiority on time. The experiment demonstrates that the new algorithm has superiority on time and accuracy with other algorithms.
引用
收藏
页码：603 / 606
页数：4
相关论文
共 50 条
  • [1] K-means Clustering Algorithm with improved Initial Center
    Zhang Chen
    Xia Shixiong
    [J]. WKDD: 2009 SECOND INTERNATIONAL WORKSHOP ON KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS, 2009, : 790 - 792
  • [2] K-means Clustering Algorithm with Refined Initial Center
    Chen, Xuhui
    Xu, Yong
    [J]. PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS, VOLS 1-4, 2009, : 2203 - 2206
  • [3] Improved initial clustering center selection algorithm for K-means
    Chen Lasheng
    Li Yuqiang
    [J]. 2017 SIGNAL PROCESSING: ALGORITHMS, ARCHITECTURES, ARRANGEMENTS, AND APPLICATIONS (SPA 2017), 2017, : 275 - 279
  • [4] K-means Optimization algorithms of initial clustering center based on regional density
    He, Yanxiang
    Cai, Rui
    Wu, Libing
    Li, Fei
    [J]. APPLIED SCIENCE, MATERIALS SCIENCE AND INFORMATION TECHNOLOGIES IN INDUSTRY, 2014, 513-517 : 478 - 482
  • [5] Improved Initial Clustering Center Selection Method for k-means Algorithm
    Xie, Qingqing
    Jiang, He
    Han, Bing
    Wang, Dongyuan
    [J]. 2018 EIGHTH INTERNATIONAL CONFERENCE ON INSTRUMENTATION AND MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC 2018), 2018, : 1092 - 1095
  • [6] K-Means Clustering Efficient Algorithm with Initial Class Center Selection
    Huang Suyu
    Hu Pingfang
    [J]. PROCEEDINGS OF THE 2018 3RD INTERNATIONAL WORKSHOP ON MATERIALS ENGINEERING AND COMPUTER SCIENCES (IWMECS 2018), 2018, 78 : 301 - 305
  • [7] A New Kind of Based on The Graph k-means Clustering Initial Center Selection Algorithm
    Zhou, Haiyan
    [J]. INDUSTRIAL INSTRUMENTATION AND CONTROL SYSTEMS, PTS 1-4, 2013, 241-244 : 2845 - 2848
  • [8] A Density-Based Method for Selection of the Initial Clustering Centers of K-means Algorithm
    Du, Xin
    Xu, Ning
    Zhou, Cailan
    Xiao, Shihui
    [J]. 2017 IEEE 2ND ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC), 2017, : 2509 - 2512
  • [9] A K-means Clustering with Optimized Initial Center Based on Hadoop Platform
    Lin, Kunhui
    Li, Xiang
    Zhang, Zhongnan
    Chen, Jiahong
    [J]. 2014 PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION (ICCSE 2014), 2014, : 263 - 266
  • [10] Improved K-means Clustering Algorithm Based on the Optimized Initial Centriods
    Wang, Shunye
    [J]. 2013 3RD INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT), 2013, : 450 - 453
12345