Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering

The emergence of big data, information technology, and social media provides an enormous amount of information about firms’ current financial health. When facing this abundance of data, decision makers must identify the crucial information to build upon an effective and operative prediction model wi...

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Vydáno v:	Computational economics Ročník 61; číslo 2; s. 715 - 741
Hlavní autoři:	Ben Jabeur, Sami, Stef, Nicolae, Carmona, Pedro
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.02.2023 Springer Springer Nature B.V Springer Verlag
Témata:	Algorithms Bankruptcy Behavioral/Experimental Economics Big Data Classification Computer Appl. in Social and Behavioral Sciences Data mining Decision makers Discriminant analysis Economic Theory/Quantitative Economics/Mathematical Methods Economics Economics and Finance Feature selection Humanities and Social Sciences Information technology Machine learning Math Applications in Computer Science Medical decision making Operations Research/Decision Theory Prediction models Predictions Social media Specification Corporate failure XGBoost Bankruptcy Machine learning Apprentissage automatique Défaillance d'entreprise Faillite
ISSN:	0927-7099, 1572-9974
On-line přístup:	Získat plný text
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