Controlled minimization of the total risk in pattern recognition

This paper is concerned with pattern-recognition where it is desired to minimize the errors in a finite operating sample fed to the recognition algorithm along with the training sample. The authors have chosen the strategy of controlled minimization of the total risk. Algorithms for the solution of the problem in the classes of linear and piecewise-linear rules are considered. The efficiency of the chosen algorithms is demonstrated by the results in medical diagnostics.