Credit scoring using support vector machines with direct search for parameters selection

DOI10.1007/s00500-008-0305-0zbMath1156.91405OpenAlexW2057125921MaRDI QIDQ1006913

Kin Keung Lai, Lean Yu, Li-Gang Zhou

Publication date: 26 March 2009

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-008-0305-0

zbMATH Keywords

Genetic algorithmSupport vector machinesCredit scoringDirect search

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items

A MODIFIED LEAST SQUARES SUPPORT VECTOR MACHINE CLASSIFIER WITH APPLICATION TO CREDIT RISK ANALYSIS, Bankruptcy prediction using SVM models with a new approach to combine features selection and parameter optimisation, Credit risk evaluation with a least squares fuzzy support vector machines classifier

Uses Software

• Matlab
• Genetic Algorithm and Direct Search Toolbox

Cites Work

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• A two-stage least cost credit scoring model
• Neural network credit scoring models
• Quantitative Methods in Credit Management: A Survey
• Benchmarking state-of-the-art classification algorithms for credit scoring
• Support vector machines for classifying and describing credit applicants: detecting typical and critical regions
• Credit Risk Evaluation with Least Square Support Vector Machine