Construction and application of innovative rating of regions using random forest technology
The published article is devoted to the urgent problem of developing models for constructing and applying an innovative rating of the country’s regions that have a radio-electronic industry (REP) branch. To overcome a number of shortcomings of known classical statistical approaches to improve the accuracy of forecasting the development of the REP industry and the adequacy of the ratings assigned to it. A version of the machine learning technology "random forest" has been developed and applied, increasing the accuracy of forecasting the development of the REP industry. The obtained ratings have been verified using data from a new observation period in order to determine the leading regions of the segments of the model’s input variables.
Authors
- Nadezhda I. Yashina
- Sergey N. Yashin (ORCID: https://orcid.org/0000-0002-7182-2808)
- Egor Koshelev (ORCID: https://orcid.org/0000-0001-5290-7913)
Institutions
- N. I. Lobachevsky State University of Nizhny Novgorod (RU)
Publication Details
- Journal
- Vestnik of Samara University Economics and Management
- Published
- 2024-12-24
- DOI
- https://doi.org/10.18287/2542-0461-2024-15-4-187-201
- Primary Topic
- Analysis of environmental and stochastic processes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Russian Science Foundation