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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">RUDN Journal of Economics</journal-id><journal-title-group><journal-title xml:lang="en">RUDN Journal of Economics</journal-title><trans-title-group xml:lang="ru"><trans-title>Вестник Российского университета дружбы народов. Серия: Экономика</trans-title></trans-title-group></journal-title-group><issn publication-format="print">2313-2329</issn><issn publication-format="electronic">2408-8986</issn><publisher><publisher-name xml:lang="en">Peoples’ Friendship University of Russia named after Patrice Lumumba (RUDN University)</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">17164</article-id><article-id pub-id-type="doi">10.22363/2313-2329-2017-25-2-242-254</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>ARTICLES</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>Статьи</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">ESTIMATION OF BANKRUPTCY RISK OF SMALL BUSINESS COMPANIES BASING METHODS OF MACHINE LEARNING</article-title><trans-title-group xml:lang="ru"><trans-title>ОЦЕНКА РИСКА БАНКРОТСТВА СУБЪЕКТОВ МАЛОГО ПРЕДПРИНИМАТЕЛЬСТВА НА ОСНОВЕ МЕТОДОВ МАШИННОГО ОБУЧЕНИЯ</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Arinichev</surname><given-names>I V</given-names></name><name xml:lang="ru"><surname>Ариничев</surname><given-names>И В</given-names></name></name-alternatives><bio xml:lang="en"><p>Arinichev I.V. Cand. Ec. Sci., Associate Professor, Department of Theoretical Economy, Kuban State University.</p></bio><bio xml:lang="ru"><p>Ариничев Игорь Владимирович, кандидат экономических наук, доцент, доцент кафедры теоретической экономики экономического факультета Кубанского государственного университета.</p></bio><email>iarinichev@gmail.com</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Bogdashev</surname><given-names>I V</given-names></name><name xml:lang="ru"><surname>Богдашев</surname><given-names>И В</given-names></name></name-alternatives><bio xml:lang="en"><p>Bogdashev I.V. Cand. Ec. Sci., Associate Professor, Department of Theoretical Economy, Kuban State University.</p></bio><bio xml:lang="ru"><p>Богдашев Илья Владимирович, кандидат экономических наук, доцент, доцент кафедры теоретической экономики экономического факультета Кубанского государственного университета.</p></bio><email>ibogdashev@gmail.com</email><xref ref-type="aff" rid="aff1"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Kuban State University</institution></aff><aff><institution xml:lang="ru">Кубанский государственный университет</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2017-12-15" publication-format="electronic"><day>15</day><month>12</month><year>2017</year></pub-date><volume>25</volume><issue>2</issue><issue-title xml:lang="en">VOL 25, NO2 (2017)</issue-title><issue-title xml:lang="ru">ТОМ 25, №2 (2017)</issue-title><fpage>242</fpage><lpage>254</lpage><history><date date-type="received" iso-8601-date="2017-10-24"><day>24</day><month>10</month><year>2017</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2017, Arinichev I.V., Bogdashev I.V.</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2017, Ариничев И.В., Богдашев И.В.</copyright-statement><copyright-year>2017</copyright-year><copyright-holder xml:lang="en">Arinichev I.V., Bogdashev I.V.</copyright-holder><copyright-holder xml:lang="ru">Ариничев И.В., Богдашев И.В.</copyright-holder><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">http://creativecommons.org/licenses/by/4.0</ali:license_ref></license></permissions><self-uri xlink:href="https://journals.rudn.ru/economics/article/view/17164">https://journals.rudn.ru/economics/article/view/17164</self-uri><abstract xml:lang="en"><p>The article deals with the methodology for constructing an algorithm for determining the probability of bankruptcy of an enterprise using machine learning methods. The advantage of this methodology is the use of not only quantitative, but also qualitative indicators of financial stability of business entities, as well as the possibility of excluding factors that have little effect on the final rating. It is assumed that the created mathematic model will be useful to representatives of small and medium-sized businesses and will provide an objective and precise picture of the financial situation of the enterprise, including current threats and the risk of bankruptcy.</p></abstract><trans-abstract xml:lang="ru"><p>В статье рассматривается методика построения алгоритма определения риска наступления банкротства предприятия с использованием методов машинного обучения. Преимуществом данной методики является использование не только количественных, но и качественных индикаторов финансовой устойчивости субъектов бизнеса, а также возможность исключения факторов, слабо влияющих на итоговый рейтинг. Предполагается, что разработанная математическая модель будет полезна представителям малого и среднего бизнеса и позволит получить объективную и точную картину о финансовом положении предприятия, текущих угрозах и риске банкротства.</p></trans-abstract><kwd-group xml:lang="en"><kwd>risk of bankruptcy</kwd><kwd>financial stability</kwd><kwd>machine learning</kwd><kwd>systems of intellectual analytics</kwd><kwd>binary tree</kwd><kwd>small business</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>риск наступления банкротства</kwd><kwd>финансовая устойчивость</kwd><kwd>машинное об-учение</kwd><kwd>системы интеллектуальной аналитики</kwd><kwd>бинарное дерево</kwd><kwd>малый бизнес</kwd></kwd-group><funding-group/></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><citation-alternatives><mixed-citation xml:lang="en">Aivazyan S.A., Bukhshtaber V.M., Enyukov I.S., Meshalkin L.D. (1989). Prikladnaya statistika. Klassifikatsiya i snizhenie razmernosti. 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