An Improved Heuristic Method for Solving Label Correspondence in Cluster Ensembles

Ensemble based methods have successfully been used in a variety of application. Recently using these methods in clustering algorithms has attracted a great deal of interest. Voting and averaging are two effective combining methods that are frequently used in multiple classifier systems. To use these methods in an unsupervised scenario (to combine multiple partitioning of data) the partitions must be relabeled first, i.e. similar partitions in different partitioning gets the same label. This phase has a great influence on the ensemble performance. In this paper a new heuristic label assignment method is proposed. The result of the Monte Carlo simulation and experimental results on real data show that the performance of ensemble method could be significantly improved using this method.

Keywords:

Clustering , ensemble clustering , cluster combination , ensemble learning