We present a preliminary study to define a comparison protocol to evaluate different quality measures used in supervised and unsupervised clustering as objective functions. We first define an order on the set of partitions to capture the common notion of a good partition towards the knowing of the ideal one. We demonstrate the efficiency of this approach by providing several experiments.
['Céline Robardet', 'Fabien Feschet', 'Nicolas Nicoloyannis']
An Experimental Study of Partition Quality Indices in Clustering