Comparing Clustering Algorithms On Wisconsin Data Set

被引：0
作者：
Erken, Mucahit [1 ]
机构：
[1] Hava Harp Okulu, Havacil & Uzay Teknol Enstitusu, Istanbul, Turkey
来源：
2016 24TH SIGNAL PROCESSING AND COMMUNICATION APPLICATION CONFERENCE (SIU) | 2016年
关键词：
Clustering; Spectral Clustering; K-Means; Girvan-Newman;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Amount and diversity of data produced and processed has been dramatically increased parallel to improvements in technology. Unfortunately produced data usually don't have any labels which may make the classification and building information process more easily. This resulted with higher importance on data clustering for builing information. In this work K-Means, Spectral Clustering and Girvan-Newman algorithms has been studied and compared on Breaast Cancer Wisconsin Data Set (BCWDS).
引用
收藏
页码：1541 / 1544
页数：4
相关论文
共 15 条
  • [1] [Anonymous], COMMUNITY DETECTION
  • [2] A Self-Adaptive Spectral Clustering Algorithm
    Cai Xiaoyan
    Dai Guanzhong
    Yang Libin
    Zhang Guoqing
    [J]. PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 4, 2008, : 551 - 553
  • [3] A comparative study of efficient initialization methods for the k-means clustering algorithm
    Celebi, M. Emre
    Kingravi, Hassan A.
    Vela, Patricio A.
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2013, 40 (01) : 200 - 210
  • [4] Dharmarajan A., 2015, INDIAN J SCI TECHNOL, V8, P1
  • [5] Girvan M., 2001, PNAS
  • [6] Detecting network communities using regularized spectral clustering algorithm
    Huang, Liang
    Li, Ruixuan
    Chen, Hong
    Gu, Xiwu
    Wen, Kunmei
    Li, Yuhua
    [J]. ARTIFICIAL INTELLIGENCE REVIEW, 2014, 41 (04) : 579 - 594
  • [7] Inkaya Tulin, 2015, SCIENCEDIRECT
  • [8] Data clustering: 50 years beyond K-means
    Jain, Anil K.
    [J]. PATTERN RECOGNITION LETTERS, 2010, 31 (08) : 651 - 666
  • [9] Kursun Olcay, 2010, SPECTRAL CLUSTERING
  • [10] Li Yang, 2004, 17 INT C PATT REC
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