Abstract
The methodology for evaluating the execution of government contracts in the energy sector by means of machine learning is presented. The signs describing performers and customers in the public procurement system were identified, the risks of fulfilling contracts on the part of customers and performers were identified, the main categories for compiling a dataset were identified and a dataset was assembled. Data problems are described, and ways to fix these problems are described. The problem of classifying the execution of government contracts is solved, a software package for intelligent forecasting of the execution of government contracts is described
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