Arguing the Validation of Dunn´s Index in Gene Clustering

Cluster validation techniques are essential tools within cluster analysis, helpful to the interpretation of clustering results. In this study, the validation ability of Dunn´s index in gene clustering was investigated with public gene expression datasets clustered by hierarchical clustering, K-means and Self-organizing maps. It was made clear that Dunn´s index would give misleading validity results for its high sensitivity to noises in the data and should not be directly used in gene clustering validation.