Individual Clustering and Homogeneous Cluster Ensemble Approaches Applied to Gene Expression Data

Abstract

Exploratory data analysis and, in particular, data clustering can significantly benefit from combining multiple data partitions – cluster ensemble. In this context, we analyze the potential of applying cluster ensemble techniques to gene expression microarray data. Our experimental results show that there is often a significant improvement in the results obtained with the use of ensemble techniques when compared to those based on the clustering techniques used individually.