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Mathematical and Computational Applications is published by MDPI from Volume 21 Issue 1 (2016). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Association for Scientific Research (ASR).
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Article

Performance of an Ensemble Clustering Algorithm on Biological Data Sets

by
Harun Pirim
1,*,
Dilip Gautam
2,
Tanmay Bhowmik
2,
Andy D. Perkins
2,
Burak Ekşioglu
1 and
Ahmet Alkan
3
1
Industrial and Systems Engineering Department, Mississippi State University, 39762, USA
2
Computer Science and Engineering Department, Mississippi State University, 39762, USA
3
University, Electrical and Electronics Engineering, 46100, Turkey
*
Author to whom correspondence should be addressed.
Math. Comput. Appl. 2011, 16(1), 87-96; https://doi.org/10.3390/mca16010087
Published: 1 April 2011
Versions Notes

Abstract

Ensemble clustering is a promising approach that combines the results of multiple clustering algorithms to obtain a consensus partition by merging different partitions based upon well-defined rules. In this study, we use an ensemble clustering approach for merging the results of five different clustering algorithms that are sometimes used in bioinformatics applications. The ensemble clustering result is tested on microarray data sets and compared with the results of the individual algorithms. An external cluster validation index, adjusted rand index (C-rand), and two internal cluster validation indices; silhouette, and modularity are used for comparison purposes.
Keywords: Ensemble Clustering; Rand Index; Silhouette Index; Modularity; Microarray Data Sets Ensemble Clustering; Rand Index; Silhouette Index; Modularity; Microarray Data Sets

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MDPI and ACS Style

Pirim, H.; Gautam, D.; Bhowmik, T.; Perkins, A.D.; Ekşioglu, B.; Alkan, A. Performance of an Ensemble Clustering Algorithm on Biological Data Sets. Math. Comput. Appl. 2011, 16, 87-96. https://doi.org/10.3390/mca16010087

AMA Style

Pirim H, Gautam D, Bhowmik T, Perkins AD, Ekşioglu B, Alkan A. Performance of an Ensemble Clustering Algorithm on Biological Data Sets. Mathematical and Computational Applications. 2011; 16(1):87-96. https://doi.org/10.3390/mca16010087

Chicago/Turabian Style

Pirim, Harun, Dilip Gautam, Tanmay Bhowmik, Andy D. Perkins, Burak Ekşioglu, and Ahmet Alkan. 2011. "Performance of an Ensemble Clustering Algorithm on Biological Data Sets" Mathematical and Computational Applications 16, no. 1: 87-96. https://doi.org/10.3390/mca16010087

APA Style

Pirim, H., Gautam, D., Bhowmik, T., Perkins, A. D., Ekşioglu, B., & Alkan, A. (2011). Performance of an Ensemble Clustering Algorithm on Biological Data Sets. Mathematical and Computational Applications, 16(1), 87-96. https://doi.org/10.3390/mca16010087

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