INTERPRETATION OF NEURAL NETWORK CLASSIFICATION RESULTS - D. V. Marshakov (Современная наука и инновации, 2022)
The paper proposes a method for extracting classification rules from an artificial neural network. The method is based on the modification of the artificial neuron, which consists in structuring data stream processed in its information field. In this case, complex multidimensional data is converted into a simpler structure of lower dimension with the possibility of subsequent trivial transformation of the results into a set of fuzzy rules of a certain type. The results of an experimental research of the proposed method are presented with the example of solving a well-known problem of multi-parameter classification. The results obtained confirm the adequacy of the proposed method, which can be used both in independent neural network pattern recognition systems and in decision support systems.