The possibilities of using machine learning methods to solve political problems

political reality is characterized by nonlinearity of processes and significant influence not only of formal, but also shadow mechanisms of interaction of the actors taking decisions - political elites and leaders. One of the most promising areas, which opens up new opportunities for studying political problems, is the synthesis of the “traditional” methodology of political analysis and methods of artificial intelligence. The paper substantiates the adequacy of the use of a decision tree for analyzing and forecasting political decisions by the example of the personnel policy of federal structures in relation to the regions of the Russian Federation.