HORÁK, Jakub, Jaromír VRBKA and Petr ŠULEŘ. Support vector machine methods and artificial neural networks used for the development of bankruptcy prediction models and their comparison. Journal of Risk and Financial Management. Basel, Switzerland: MDPI, vol. 13, No 3, p. nestránkováno, 15 pp. ISSN 1911-8066. doi:10.3390/jrfm13030060. 2020.
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Basic information
Original name Support vector machine methods and artificial neural networks used for the development of bankruptcy prediction models and their comparison
Name in Czech Metody support vector machine a umělé neuronové sítě používané při vývoji modelů predikce bankrotu a jejich srovnání
Authors HORÁK, Jakub (203 Czech Republic, guarantor, belonging to the institution), Jaromír VRBKA (203 Czech Republic, belonging to the institution) and Petr ŠULEŘ (203 Czech Republic, belonging to the institution).
Edition Journal of Risk and Financial Management, Basel, Switzerland, MDPI, 2020, 1911-8066.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 50200 5.2 Economics and Business
Country of publisher Switzerland
Confidentiality degree is not subject to a state or trade secret
WWW URL
RIV identification code RIV/75081431:_____/20:00001754
Organization unit Institute of Technology and Business in České Budějovice
Doi http://dx.doi.org/10.3390/jrfm13030060
UT WoS 000523491700001
Keywords (in Czech) neuronové sítě; support vector machine; bankrotní model; predikce; bankrot
Keywords in English neural networks; support vector machine; bankruptcy model; prediction; bankruptcy
Tags FIP_2, RIV20, WOS
Changed by Changed by: Kateřina Nygrýnová, učo 23736. Changed: 4/6/2020 11:21.
Abstract
The objective of this paper is to create a model for predicting potential bankruptcy of companies using suitable classification methods, namely Support Vector Machine and artificial neural networks, and to evaluate the results of the methods used.
Abstract (in Czech)
Cílem této práce je vytvořit model pro predikci možného bankrotu společností pomocí vhodných klasifikačních metod, konkrétně Support Vector Machine a umělých neuronových sítí, a zhodnotit výsledky použitých metod.
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