A New Clustering Ensemble Framework

Parvin, Hamid; Alinejad-Rokny, Hamid; Parvin, Sajad

doi:10.18576/ijlms/010103

A New Clustering Ensemble Framework

Document Type : Original Article

Authors

¹ Department of Computer Engineering, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran

² School 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

10.18576/ijlms/010103

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