Class: A nonparametric clustering algorithm

Abstract The paper describes a nonparametric method for clustering of large data problems. The algorithm based on the ISODATA technique, calculates all required thresholds from the actual data, thus eliminating a priori estimates. Empirical derivation of the set of rules for calculating these parameters is presented. Results of using the technique on a number of artificial and real data samples are discussed.