Preliminary Data Analysis and Feature Construction in Financial and Economic Information Processing Tasks
- Authors: Semenova P.A.1, Grineva N.V.1, Mikhaylova S.S.1
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Affiliations:
- Financial University under the Government of the Russian Federation
- Issue: Vol 19, No 3 (2023)
- Pages: 141-152
- Section: Mathematical, Statistical and Instrumental Methods in Economics
- URL: https://journals.eco-vector.com/2541-8025/article/view/568338
- EDN: https://elibrary.ru/CALJPF
- ID: 568338
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Open Access
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Abstract
Machine learning is the main field of artificial intelligence. This contributes to a new stage in the development of the field of information technology, since now the computer is able to switch to self-learning mode without explicit programming. The aim of the study was to find the optimal set of exogenous variables that ensures the best quality of the model in the task of forecasting output volumes. As a result, several methods of constructing new attributes are implemented and the main aspects in the preprocessing of data from this subject area are highlighted.
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About the authors
Polina A. Semenova
Financial University under the Government of the Russian Federation
Author for correspondence.
Email: 195229@edu.fa.ru
ORCID iD: 0009-0000-4835-5319
Faculty of Information Technology and Big Data Analysis
Russian Federation, MoscowNatalia V. Grineva
Financial University under the Government of the Russian Federation
Email: ngrineva@fa.ru
ORCID iD: 0000-0001-7647-5967
SPIN-code: 1140-9636
Cand. Sci. (Econ.), Associate Professor, Associate Professor of the Department of Data Analysis and Machine Learning
Russian Federation, MoscowSvetlana S. Mikhaylova
Financial University under the Government of the Russian Federation
Email: ssmihajlova@fa.ru
ORCID iD: 0000-0001-9183-8519
SPIN-code: 9697-3928
Dr. Sci. (Econ.), Professor, Professor of the Department of Data Analysis and Machine Learning
Russian Federation, MoscowReferences
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