Parvin, H., Alinejad-Rokny, H., Parvin, S. (2013). A New Clustering Ensemble Framework. test, 1(1), 17-23. doi: 10.18576/ijlms/010103
Hamid Parvin; Hamid Alinejad-Rokny; Sajad Parvin. "A New Clustering Ensemble Framework". test, 1, 1, 2013, 17-23. doi: 10.18576/ijlms/010103
Parvin, H., Alinejad-Rokny, H., Parvin, S. (2013). 'A New Clustering Ensemble Framework', test, 1(1), pp. 17-23. doi: 10.18576/ijlms/010103
Parvin, H., Alinejad-Rokny, H., Parvin, S. A New Clustering Ensemble Framework. test, 2013; 1(1): 17-23. doi: 10.18576/ijlms/010103

A New Clustering Ensemble Framework

International Journal of Learning Management Systems
Volume 1, Issue 1, January 2013, Pages 17-23    PDF (518.55 K)
Document Type: Original Article
DOI: 10.18576/ijlms/010103
Authors
Hamid Parvin1; Hamid Alinejad-Rokny2; Sajad Parvin1
1Department of Computer Engineering, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran
2School of Electrical Engineering and Computer Science, Faculty of Engineering and Built Environment, The University of Newcastle, Callaghan, NSW, Australia 3Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle, Callaghan, NSW, Australia
Abstract
A new criterion for clusters validation is proposed in the paper and based on the new cluster validation criterion a clustering ensmble framework is proposed. The main idea behind the framework is to extract the most stable clusters in terms of the defined criteria. Employing this new cluster validation criterion, the obtained ensemble is evaluated on some well-known and standard data sets. The empirical studies show promising results for the ensemble obtained using the proposed criterion comparing with the ensemble obtained using the standard clusters validation criterion.

Keywords
 Clustering Ensemble; Stability Measure; Cluster Evaluation
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