Abstract
Studies of abnormal values play an important role in understanding the generating processes and are one of the key ones in financial analysis and forecasting. This article is devoted to the study of anomalies in federal budget revenues. Based on statistical data for the period from 2008 to 2022, abnormal values of budget revenues in different time periods were revealed using statistical models and machine learning methods, their advantages and disadvantages are shown. Practical recommendations on the use of machine learning methods to identify anomalies in the field of public finance are given.
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