A randomized algorithm for estimating the number of clusters
Oleg Nikolaevich Granichin, Dmitry S. Shalymov, Renata Avros, Zeev Volkovich · Automation and Remote Control · 2011
Clustering is actively studied in such fields as statistics, pattern recognition, machine training, et al. A new randomized algorithm is suggested and established for finding the number of clusters in the set of data, the efficiency of which is demonstrated by examples of simulation modeling on synthetic data with thousands of clusters.