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NSPDK_candidateClusters (version
for single iteration- NO, for multiple-YES
to minimize memory usage
by default true
by default true
-knn num
-nhf num
The number of hash functions is increased by this value after each iteration.

What it does

Copmutes global feature index and returns top dense sets. The candidate clusters are chosen as the top ranking neighborhoods provided that the size of their overlap is below a specified threshold. For more information see Fast neighborhood subgraph pairwise distance kernel paper.