A randomized algorithm for estimating the number of clusters

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.

Presented by the member of Editorial Board: A. V. Nazin