Work

Construction and application of innovative rating of regions using random forest technology

Year: 2024

Type: article

Abstract: 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.

Source: Vestnik of Samara University Economics and Management

DOI: 10.18287/2542-0461-2024-15-4-187-201

Authors: Sergey N. Yashin, Nadezhda I. Yashina, Egor V. Koshelev

Institution: N. I. Lobachevsky State University of Nizhny Novgorod

Language: English

Topic: Economic Development and Regional Competitiveness

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funder: Russian Science Foundation