Two-stage genetic programming (2SGP) for the credit scoring model

Credit scoring models have been widely studied in the areas of statistics, machine learning, and artificial intelligence (AI). Many novel approaches such as artificial neural networks (ANNs), rough sets, or decision trees have been proposed to increase the accuracy of credit scoring models. Since an...

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Veröffentlicht in:	Applied mathematics and computation Jg. 174; H. 2; S. 1039 - 1053
Hauptverfasser:	Huang, Jih-Jeng, Tzeng, Gwo-Hshiung, Ong, Chorng-Shyong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY Elsevier Inc 15.03.2006 Elsevier
Schlagworte:	Applied sciences Artificial intelligence Artificial neural network (ANN) Computer science; control theory; systems Credit scoring model Decision trees Exact sciences and technology Learning and adaptive systems Mathematics Numerical analysis Numerical analysis. Scientific computation Numerical methods in mathematical programming Numerical methods in mathematical programming, optimization and calculus of variations Rough sets Sciences and techniques of general use Two-stage genetic programming (2SGP) Artificial neural network (ANN) Credit scoring model Decision trees Two-stage genetic programming (2SGP) Rough sets Decision tree Discriminant function Statistical method Accuracy Numerical analysis Applied mathematics Genetic programming Artificial intelligence
ISSN:	0096-3003, 1873-5649
Online-Zugang:	Volltext
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