Towards a standard methodology to evaluate internal cluster validity indices

The evaluation and comparison of internal cluster validity indices is a critical problem in the clustering area. The methodology used in most of the evaluations assumes that the clustering algorithms work correctly. We propose an alternative methodology that does not make this often false assumption. We compared 7 internal cluster validity indices with both methodologies and concluded that the results obtained with the proposed methodology are more representative of the actual capabilities of the compared indices.

Research highlights
► Internal cluster validity indices (CVIs) are used to evaluate cluster partitions.
► The usual CVI comparison methodology makes an assumption which is often incorrect.
► We propose an alternative methodology to compare CVIs that obtains better results.