Use of machine learning for evaluating investment activity

Krichevskiy M.L.¹, Martynova Yu.A.¹
¹ Санкт-Петербургский государственный университет аэрокосмического приборостроения, Russia

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Journal paper

Russian Journal of Innovation Economics ^{(РИНЦ, ВАК)}
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Volume 9, Number 4 (October-December 2019)

Citation:

Indexed in Russian Science Citation Index: https://elibrary.ru/item.asp?id=42555591
Cited: 6 by 30.01.2024

Abstract:
The results of the application of machine learning methods suitable for evaluating the investment activity of various regions of Russia are presented. The database used in this work was the Rosstat report for 2018, which contains information on the investment activity of all Russian regions. The solution to the problem is brought to the receipt of information about the class to which this or that region belongs. The machine learning algorithms used in the work were taken from the software product MatLab 2018b. As a result of the study, in order to solve the problem, the best methods for classification accuracy were selected, with which you can judge the activities of Russian regions in the field of investment. It is shown that the results obtained are used to form an assessment of whether a new observation belongs to a specific category.

Keywords: Key words: investment activity, machine learning, cluster analysis, classification methods, determining the class of regions

JEL-classification: С45, С65, D81

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