Computer implemented, fast, approximate clustering based on sampling

摘要

(1) An approximate center-based clustering that utilizes sampling to cluster a set of n points to identify k>0 centers with quality assurance, but without the drawbacks of sample size and running time dependence on n. (2) An approximate conceptual clustering algorithm that utilizes sampling to identify k disjoint conjunctions with novel quality assurance, also without the drawbacks of sample size and running time dependence on n.