  We consider the simultaneous clustering of rows and columns of a matrix and
more particularly the ability to measure the agreement between two
co-clustering partitions. The new criterion we developed is based on the
Adjusted Rand Index and is called the Co-clustering Adjusted Rand Index named
CARI. We also suggest new improvements to existing criteria such as the
Classification Error which counts the proportion of misclassified cells and the
Extended Normalized Mutual Information criterion which is a generalization of
the criterion based on mutual information in the case of classic
classifications. We study these criteria with regard to some desired properties
deriving from the co-clustering context. Experiments on simulated and real
observed data are proposed to compare the behavior of these criteria.
