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Information 2019, 10(2), 59; https://doi.org/10.3390/info10020059

A Three-Way Clustering Method Based on Ensemble Strategy and Three-Way Decision

1
School of Science, Jiangsu University of Science and Technology, Zhenjiang 212003, China
2
College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang 050024, China
3
School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang 212003, China
4
School of Naval Architecture and Ocean Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China
*
Author to whom correspondence should be addressed.
Received: 12 December 2018 / Revised: 27 January 2019 / Accepted: 10 February 2019 / Published: 14 February 2019
(This article belongs to the Section Information Theory and Methodology)
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Abstract

Three-way decision is a class of effective ways and heuristics commonly used in human problem solving and information processing. As an application of three-way decision in clustering, three-way clustering uses core region and fringe region to represent a cluster. The identified elements are assigned into the core region and the uncertain elements are assigned into the fringe region in order to reduce decision risk. In this paper, we propose a three-way clustering algorithm based on the ideas of cluster ensemble and three-way decision. In the proposed method, we use hard clustering methods to produce different clustering results and labels matching to align all clustering results to a given order. The intersection of the clusters with the same labels are regarded as the core region. The difference between the union and the intersection of the clusters with the same labels are regarded as the fringe region of the specific cluster. Therefore, a three-way clustering is naturally formed. The results on UCI data sets show that such a strategy is effective in improving the structure of clustering results. View Full-Text
Keywords: three-way decision; three-way clustering; cluster ensemble; label matching three-way decision; three-way clustering; cluster ensemble; label matching
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Wang, P.; Liu, Q.; Xu, G.; Wang, K. A Three-Way Clustering Method Based on Ensemble Strategy and Three-Way Decision. Information 2019, 10, 59.

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