Model Order Selection for Clustering

Stability based methods for model order selection in clustering problems (Valentini, G (2007), ). Using multiple perturbations of the data the stability of clustering solutions is assessed. Different perturbations may be used: resampling techniques, random projections and noise injection. Stability measures for the estimate of clustering solutions and statistical tests to assess their significance are provided.