Results of analysis of machine learning practice for training effective model of bankruptcy forecasting in emerging markets

dc.contributor.authorKrasniuk, Maksym
dc.contributor.authorКраснюк, Максим Тарасович
dc.contributor.authorTkalenko, Antonina
dc.contributor.authorKrasniuk, Svitlana
dc.date.accessioned2025-05-21T11:01:35Z
dc.date.available2025-05-21T11:01:35Z
dc.date.issued2021-04-09
dc.identifier.citationKrasnyuk M. Results of analysis of machine learning practice for training effective model of bankruptcy forecasting in emerging markets / Maxim Krasnyuk, Antonina Tkalenko, Svitlana Krasniuk // Multidisziplinäre Forschung: Perspektiven, Probleme und Muster : der Sammlung wissenschaftlicher Arbeiten «ΛΌГOΣ» zu den materialien der I internationalen wissenschaftlich-praktischen Konferenz, Wien, Republik Österreich, April 9, 2021 : in 3 b. / [org. com.: Holdenblat M. (vorsitzender)]. – Wien : List Verlag. in Ullstein Buchverlage GmbH ; Vinnytsia : Europäische Wissenschaftsplattform, 2021. – B. 1. – P. 28–30.
dc.identifier.doihttps://doi.org/10.36074/logos-09.04.2021.v1.07
dc.identifier.urihttps://ir.kneu.edu.ua/handle/2010/50392
dc.language.isoen
dc.publisherEuropean Scientific Platform
dc.titleResults of analysis of machine learning practice for training effective model of bankruptcy forecasting in emerging markets
dc.typeArticle
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Wien_28-30.pdf
Size:
270.92 KB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: