A corporate credit rating model using multi-class support vector machines with an ordinal pairwise partitioning approach
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Publication:1761095
DOI10.1016/j.cor.2011.06.023zbMath1251.91068OpenAlexW2163094209MaRDI QIDQ1761095
Publication date: 15 November 2012
Published in: Computers \& Operations Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cor.2011.06.023
support vector machinesmulti-class classificationcorporate credit ratingordinal pairwise partitioning
Learning and adaptive systems in artificial intelligence (68T05) Quadratic programming (90C20) Corporate finance (dividends, real options, etc.) (91G50) Credit risk (91G40)
Related Items (9)
An extended EDAS method under four-branch fuzzy environments and its application in credit evaluation for micro and small entrepreneurs ⋮ Company rating with support vector machines ⋮ A novel dynamic credit risk evaluation method using data envelopment analysis with common weights and combination of multi-attribute decision-making methods ⋮ Sparse concordance‐based ordinal classification ⋮ Machine learning in corporate credit rating assessment using the expanded audit report ⋮ A corporate credit rating model using support vector domain combined with fuzzy clustering algorithm ⋮ Exploitation of Pairwise Class Distances for Ordinal Classification ⋮ Unnamed Item ⋮ Performance evaluation of least-squares probabilistic classifier for corporate credit rating classification problem
Uses Software
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