A novel framework for discovering robust cluster results

Authors:
Hye-Sung Yoon;Sang-Ho Lee;Sung-Bum Cho;Ju Han Kim
Affiliations:
Department of Computer Science and Engineering, Ewha Womans University, Seoul, Korea;Department of Computer Science and Engineering, Ewha Womans University, Seoul, Korea;Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, Korea;Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, Korea
Venue:
DS'06 Proceedings of the 9th international conference on Discovery Science
Year:
2006

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Abstract

We propose a novel method, called heterogeneous clustering ensemble (HCE), to generate robust clustering results that combine multiple partitions (clusters) derived from various clustering algorithms. The proposed method combines partitions of various clustering algorithms by means of newly-proposed the selection and the crossover operation of the genetic algorithm (GA) during the evolutionary process.