External Indices for Rough Clustering

Clustering external indices are used to compare the clustering result with a given gold standard, represented (in the classical case) by a partition of the dataset. Rough clustering on the other hand splits the dataset in subsets with uncertain boundaries such that different clusters may overlap, i.e., the result is a covering instead of a partition.

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