Clustering Ensembles Using Evolutionary Algorithm

Abstract

Data clustering is an important task and applied in various real-world problems. Since, not a single clustering algorithm is able to identify all types of cluster shapes and structures. Ensemble clustering was proposed to combine different partitions of the same data generated by multiple clustering algorithms. The key idea of most ensemble clustering algorithms is to find a partition that is consistent with most of the available partitions of the input data. Currently, there is no single clustering algorithm available to find all types of cluster shapes and structures. Therefore, in this paper, we propose an ensemble clustering algorithm in order to produce accurate clusters. And also, we enhance the single-objective PCE formulation; with the ultimate goal of providing more effective formulations capable of reducing the accuracy gap. The experimental evidence has demonstrated the significance of our proposed heuristics.

Authors and Affiliations

Purushothaman B

Keywords

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  • EP ID EP19636
  • DOI -
  • Views 264
  • Downloads 4

How To Cite

Purushothaman B (2015). Clustering Ensembles Using Evolutionary Algorithm. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 3(2), -. https://europub.co.uk/articles/-A-19636