Operational analysis of k-medoids and k-means algorithms on noisy data

被引：0

作者：

Manjoro, Wellington Simbarashe ^{[1
]}

Dhakar, Mradul ^{[2
]}

Chaurasia, Brijesh Kumar ^{[2
]}

机构：

[1] ITM Gwalior Univ, Gwalior, India

[2] ITM Gwalior Univ, Dept Comp Sci & Engn, Gwalior, India

来源：

2016 INTERNATIONAL CONFERENCE ON COMMUNICATION AND SIGNAL PROCESSING (ICCSP), VOL. 1 | 2016年

关键词：

clustering; k-means; k-medoids; PAM; noise; outlier;

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：

Clustering is applied to many applications and the decision with regards to which algorithm to use is dependent on the nature of the task to be carried out. Before choosing which clustering algorithm to use one needs to be aware of the nature of the task to be done and then determine the algorithm accordingly, based on the capabilities and performance metrics of that algorithm. This paper makes an operational comparison of the k-means and k-medoids clustering algorithms focusing on the effect of noise and outliers on each algorithm.

引用

页码：1500 / 1505

页数：6

共 10 条

[1]

Bhoomija M.D., 2008, Journal of Computer Applications, V1, P18

[2] A Survey of Evolutionary Algorithms for Clustering [J].

Hruschka, Eduardo Raul ;

Campello, Ricardo J. G. B. ;

Freitas, Alex A. ;

de Carvalho, Andre C. Ponce Leon F. .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, 2009, 39 (02) :133-155

[3]

Madhulatha TS, 2011, COMM COM INF SC, V198, P472

[4]

Raghuwanshi ShailendraSingh., 2012, International Journal of Com- puting, Communications and Networking, V1

[5]

Rajarajeswari A., 2015, Int. J. Adv. Found. Res. Comput. (IJAFRC), V2, P7

[6]

Shah S., 2012, Proceedings of the 2012 International Conference on Communication Systems and Network Technologies (CSNT 2012), P435, DOI 10.1109/CSNT.2012.100

[7]

Singh R. V., 2011, 2011 International Conference on Recent Trends in Information Technology (ICRTIT 2011), P717, DOI 10.1109/ICRTIT.2011.5972376

[8]

Tiwari Mahendra., 2012, INT J ENG RES DEV, V4, P69

[9]

Velmurugan T., 2010, Journal of Computer Sciences, V6, P363, DOI 10.3844/jcssp.2010.363.368

[10] K-means Clustering Algorithm with improved Initial Center [J].

Zhang Chen ;

Xia Shixiong .

WKDD: 2009 SECOND INTERNATIONAL WORKSHOP ON KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS, 2009, :790-792

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