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With the aim to propose a non parametric hypothesis test, this paper carriesout a study on the Matching Error (ME), a comparison index of two partitionsobtained from the same data set, using for example two clustering methods. Thisindex is related to the misclassifica-tion error in supervised learning. Someproperties of the ME and, especially, its distribution function for the case oftwo independent partitions are analyzed. Extensive simulations show theefficiency of the ME and we propose a hypothesis test based on it.

Comparing partitions through the Matching Error