Abstract
A method for determining the parameters of a fuzzy discriminant function from a set of diagnostic test results is considered. These tests are the basis of the training sample for controlling the level of knowledge in nominal rating scales in automated learning systems. The fuzziness of measuring the results of solving control problems, as well as the classification of objects in the training sample, is taken into account. The method has a specific versatility and allows building similar diagnostic procedures for objects of different physical nature.
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