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Network science investigates methodologies that summarise relational data toobtain better interpretability. Identifying modular structures is a fundamentaltask, and assessment of the coarse-grain level is its crucial step. Here, wepropose principled, scalable, and widely applicable assessment criteria todetermine the number of clusters in modular networks based on the leave-one-outcross-validation estimate of the edge prediction error.

Cross-validation estimate of the number of clusters in a network