The paper describes new approaches to statistical pattern recognition. All presented methods are based on a distance function. The properties of these methods and their usefulness are illustrated on real problems. Some tasks with small and very large training sets are described to shown an effectiveness of the proposed approaches. There is no one universal method that would be satisfactory for all object classification problems. That's why several methods have been demonstrated.
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