FORECASTING THE INVESTMENT INDICATORS ON THE BASIS OF SOLUTION TREES
https://doi.org/10.21686/2413-2829-2016-6-86-95
Abstract
The article shows specific features of short-term forecast models, which were realized on the basis of the solution trees method applied to regression task. The authors provide the description of key characteristics of the trees solution method using CART algorithm. The necessity to use alternative intellectual methods of forecasting was grounded due to more difficult and highly uncertain nature of political and social-economic processes. The mechanism of final summing-up of forecasts was described. The authors put forward several variants of implementing models designed by Python programming. Computer experiments were conducted to adjust model parameters that can guarantee acceptable results in forecasting investment indicators.
About the Authors
Olga V. Kitova
Plekhanov Russian University of Economics
Russian Federation
Russian Federation
Doctor of Economics, Professor, Head of the Department for Information Science of the PRUE
36 Stremyanny Lane, Moscow, 117997, Russian Federation
Igor B. Kolmakov
Plekhanov Russian University of Economics
Russian Federation
Russian Federation
Doctor of Economics, Professor of the Department for Information Science of the PRUE
36 Stremyanny Lane, Moscow, 117997, Russian Federation
Ilya A. Penkov
Plekhanov Russian University of Economics
Russian Federation
Russian Federation
Post-Graduate Student of the Department for Information Science of the PRUE
36 Stremyanny Lane, Moscow, 117997, Russian Federation
References
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Review
For citations:
Kitova O.V., Kolmakov I.B., Penkov I.A. FORECASTING THE INVESTMENT INDICATORS ON THE BASIS OF SOLUTION TREES. Vestnik of the Plekhanov Russian University of Economics. 2016;(6):86-95. (In Russ.) https://doi.org/10.21686/2413-2829-2016-6-86-95
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