Combining hierarchical clusterings using min-transitive closure

Abdolreza Mirzaei, Mohammad Rahmati
2008 Pattern Recognition (ICPR), Proceedings of the International Conference on  
In the past, clusterings combination approaches are based on "flat" clustering algorithms, i.e. algorithms that operate on non-hierarchical clustering schemes. These approaches, once applied to a hierarchical clusterings combination problem, are not capable of taking advantage of the information inherent in the input clusterings hierarchy, and may thus be suboptimal. In this paper, a new hierarchical clusterings combination framework is proposed for combining multiple dendrograms directly. In
more » ... is framework, the description matrices of the primary hierarchical clusterings are aggregated into a transitive consensus matrix with which the final clustering is formed. Experiments on real-world datasets indicate that this framework provides solutions of improved quality.
doi:10.1109/icpr.2008.4761275 dblp:conf/icpr/MirzaeiR08 fatcat:3uyj3dwm3ffenftmbqnetcuj7q