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When the aim is to evaluate the solution of a fuzzy clustering algorithm, the computation of the adjusted version of the Rand index requires converting the soft partitions to hard partitions.Furthermore, in comparing two fuzzy partitions from two different clustering methods, an external validation index should satisfy two desirable properties: \textit{(i)} reflexivity, and \textit{(ii)} a proper interpretation of correction for agreement due to chance. In this paper, we define an extension of the commonly used adjusted Rand index to fuzzy partitions based on normalized degree of concordance.