Instruments and Systems: Monitoring, Control, and Diagnostics Annotation << Back A Numerical Study of the Effectiveness of Machine Learning in the Tasks of Forecasting the Significance of the Significance of Critical Information Infrastructure Objects M.YU. RYTOV, YU.YU. GROMOV, N.O. MUSIENKO, YU.A. GUBSKOV, YU.V. MININ A numerical study of the effectiveness of machine learning in the tasks of predicting the significance of the significance of critical information infrastructure objects (KII) was carried out, within the framework of which the implementation of the prognosis methodology in the software environment, the study of the applicability of machine learning in the tasks of the significance of the significance of KII objects, and the study of the results of forecasting during The use of different quality metrics, the study of the effect of changing the proportion of the control sample on the quality of the forecast, an assessment of the influence of signifi cant features on the results of forecasting, in the formation of the initial data sample. Keywords: information security, critical information infrastructure, signifi cance criteria, information technology, cybersecurity, facilities of the fuel and energy complex, software, machine learning, forecasting models. DOI: 10.25791/pribor.10.2022.1366 Pp. 29-44.