Affiliations: [a] Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran | [b] Computer Science Department, Collage of Engineering, Wayne State University, Detroit, MI, USA | [c] Image Processing and Pattern Recognition Laboratory, Computer Engineering and Information Technology Department, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
Correspondence:
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Corresponding author: Abdolreza Mirzaei, Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran. E-mail:mirzaei@cc.iut.ac.ir
Abstract: Various ensemble methods are proposed to
aggregate hierarchical clusterings. These methods combine a set of
hierarchical clusterings into a single representative clustering with an
improved quality. The quality of this representative hierarchical clustering
intensively depends on the aggregation operator (aggregator) used in the
combination. However, choosing from the large pool of aggregators is a
challenging task. To facilitate this task, in this paper, we first introduce
aggregator types, triangular norms and averaging operators, and then compile
a list of main properties and parametric characteristics of these
aggregators. An extra property which is needed in hierarchical clustering
combination is also defined. Thereafter, a set of experiments is designed to
elect the optimized hierarchy aggregator from the variety of these
aggregators. The out coming results from the experiments are proved to be
compatible with the previous applications in the field of hierarchical
clustering ensembles.
