Open AccessMACHINE LEARNING AS A CORPORATION'S TOOL FOR SELECTION OF SUPPLIERS
Author(s) -
В. В. Баклушинский,
Е. В. Пустынникова
Publication year - 2019
Publication title -
vestnik universiteta
Language(s) - English
Resource type - Journals
eISSN - 2686-8415
pISSN - 1816-4277
DOI - 10.26425/1816-4277-2019-9-48-53
Subject(s) - currency , scope (computer science) , corporation , computer science , machine learning , field (mathematics) , reliability (semiconductor) , selection (genetic algorithm) , artificial intelligence , theme (computing) , business , finance , economics , world wide web , power (physics) , physics , mathematics , quantum mechanics , pure mathematics , monetary economics , programming language
In the economics and finance, machine learning methods have spread when solving the problems of consumer behavior research and in currency and securities trading. However, they are poorly developed in dealing with issues related to interaction between enterprises. The article presents the results of the compilation and testing of machine learning models, created to assess the reliability of enterprises as suppliers. According to the analysis, carried out in the article, machine learning methods are applicable when conducting supplier evaluations. This article has been written on the theme of expanding the scope of machine learning in the field of analysis of the behavior of commercial enterprises.