Analysis of an ensemble algorithm for clustering cancer data

Dengyuan Wu; Li Sheng; Eric Xu; Kai Xing; Dechang Chen

doi:10.1109/BIBMW.2012.6470233

Analysis of an ensemble algorithm for clustering cancer data

Dengyuan Wu^*, Li Sheng, Eric Xu, Kai Xing, Dechang Chen

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

In this paper, we present an analysis of the ensemble algorithm of clustering of cancer data (EACCD) by Chen et al. Using a breast cancer dataset, we demonstrate the effectiveness of EACCD in capturing differences among survival curves. We also investigate the impact of different settings in EACCD and compare EACCD with several other clustering approaches.

Original language	English
Title of host publication	Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012
Pages	754-755
Number of pages	2
DOIs	https://doi.org/10.1109/BIBMW.2012.6470233
State	Published - 2012
Externally published	Yes
Event	2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012 - Philadelphia, PA, United States Duration: 4 Oct 2012 → 7 Oct 2012

Publication series

Name	Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012

Conference

Conference	2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012
Country/Territory	United States
City	Philadelphia, PA
Period	4/10/12 → 7/10/12

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10.1109/BIBMW.2012.6470233

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Wu, D., Sheng, L., Xu, E., Xing, K., & Chen, D. (2012). Analysis of an ensemble algorithm for clustering cancer data. In Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012 (pp. 754-755). Article 6470233 (Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012). https://doi.org/10.1109/BIBMW.2012.6470233

@inproceedings{814b3aa373914e8daea0fdb62c187cea,

title = "Analysis of an ensemble algorithm for clustering cancer data",

abstract = "In this paper, we present an analysis of the ensemble algorithm of clustering of cancer data (EACCD) by Chen et al. Using a breast cancer dataset, we demonstrate the effectiveness of EACCD in capturing differences among survival curves. We also investigate the impact of different settings in EACCD and compare EACCD with several other clustering approaches.",

author = "Dengyuan Wu and Li Sheng and Eric Xu and Kai Xing and Dechang Chen",

year = "2012",

doi = "10.1109/BIBMW.2012.6470233",

language = "English",

isbn = "9781467327466",

series = "Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012",

pages = "754--755",

booktitle = "Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012",

note = "2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012 ; Conference date: 04-10-2012 Through 07-10-2012",

}

Wu, D, Sheng, L, Xu, E, Xing, K & Chen, D 2012, Analysis of an ensemble algorithm for clustering cancer data. in Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012., 6470233, Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012, pp. 754-755, 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012, Philadelphia, PA, United States, 4/10/12. https://doi.org/10.1109/BIBMW.2012.6470233

Analysis of an ensemble algorithm for clustering cancer data. / Wu, Dengyuan; Sheng, Li; Xu, Eric et al.
Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012. 2012. p. 754-755 6470233 (Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In this paper, we present an analysis of the ensemble algorithm of clustering of cancer data (EACCD) by Chen et al. Using a breast cancer dataset, we demonstrate the effectiveness of EACCD in capturing differences among survival curves. We also investigate the impact of different settings in EACCD and compare EACCD with several other clustering approaches.

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DO - 10.1109/BIBMW.2012.6470233

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Wu D, Sheng L, Xu E, Xing K, Chen D. Analysis of an ensemble algorithm for clustering cancer data. In Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012. 2012. p. 754-755. 6470233. (Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012). doi: 10.1109/BIBMW.2012.6470233

Analysis of an ensemble algorithm for clustering cancer data

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