This paper combines information systems with fuzzy pattern recognition and proposes an improved fuzzy pattern decision-making method based on it. The decision attributes and conditional attributes are selected according to the decision purpose, and the correlation coefficients of the decision attributes and conditional attributes are derived by combining the original attribute values using the correlation method to determine the weights of each conditional attribute, while the weights of the decision attributes are determined by the decision maker. The standard set and the set to be measured in the fuzzy model are constructed using the affiliation functions of the different attributes. The degree of proximity between the criterion set and the set to be tested is calculated and the solution that best exploits the advantages of the current stage is selected as the optimal solution. The introduction of an information system into the pattern recognition model simplifies the decision-making process by reducing the number of attributes that may be missed in the decision and retaining the characteristics of the original attributes.
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