Genetic algorithm-based heuristic for feature selection in credit risk assessment

Expert Systems with Applications - Tập 41 - Trang 2052-2064 - 2014
Stjepan Oreski1, Goran Oreski1
1Bank of Karlovac, I.G. Kovacica 1, 47000 Karlovac, Croatia

Tài liệu tham khảo

Aha, 1996, 199 Akkoç, 2012, An empirical comparison of conventional techniques, neural networks and the three stage hybrid Adaptive Neuro Fuzzy Inference System (ANFIS) model for credit scoring analysis: The case of Turkish credit card data, European Journal of Operational Research, 222, 168, 10.1016/j.ejor.2012.04.009 Bache, K., & Lichman, M. (2013). UCI machine learning repository. Irvine, CA: University of California, School of Information and Computer Science. <http://archive.ics.uci.edu/ml>. Bäck, 1997 BIS. Basel III: a global regulatory framework for more resilient banks and banking systems. (2011). Basel Committee on Banking Supervision, Bank for International Settlements, Basel. ISBN print: 92-9131-859-0. <http://www.bis.org/publ/bcbs189.pdf>. Danenas, 2011, Credit risk evaluation model development using support vector based classifiers, Procedia Computer Science, 4, 1699, 10.1016/j.procs.2011.04.184 Finlay, 2011, Multiple classifier architectures and their application to credit risk assessment, European Journal of Operational Research, 210, 368, 10.1016/j.ejor.2010.09.029 Goldberg, 1988, Genetic algorithms and machine learning, Machine Learning, 3, 95, 10.1023/A:1022602019183 Huang, 2007, Credit scoring with a data mining approach based on support vector machines, Expert Systems with Applications, 33, 847, 10.1016/j.eswa.2006.07.007 Jin, 2012, Attribute selection method based on a hybrid BPNN and PSO algorithms, Applied Soft Computing, 12, 2147, 10.1016/j.asoc.2012.03.015 Khandani, 2010, Consumer credit-risk models via machine-learning algorithms, Journal of Banking & Finance, 34, 2767, 10.1016/j.jbankfin.2010.06.001 Khashman, 2010, Neural networks for credit risk evaluation: investigation of different neural models and learning schemes, Expert Systems with Applications, 37, 6233, 10.1016/j.eswa.2010.02.101 Kira, 1992, A practical approach to feature selection, 249 Kohavi, 1997, Wrappers for feature subset selection, Artificial Intelligence, 97, 273, 10.1016/S0004-3702(97)00043-X Li, 2011, Initialization strategies to enhancing the performance of genetic algorithms for the p-median problem, Computers & Industrial Engineering, 61, 1024, 10.1016/j.cie.2011.06.015 Maaranen, 2004, Quasi-random initial population for genetic algorithms, Computers and Mathematics with Applications, 47, 1885, 10.1016/j.camwa.2003.07.011 Malhotra, 2003, Evaluating consumer loans using neural networks, Omega, 31, 83, 10.1016/S0305-0483(03)00016-1 McCall, 2005, Genetic algorithms for modeling and optimization, Journal of Computational and Applied Mathematics, 184, 205, 10.1016/j.cam.2004.07.034 Michalewicz, 1998 Mitchell, 1996 Myers, 2003 Oreski, 2012, Hybrid system with genetic algorithm and artificial neural networks and its application to retail credit risk assessment, Expert Systems with Applications, 39, 12605, 10.1016/j.eswa.2012.05.023 Pezzella, 2007, A genetic algorithm for the flexible job-shop scheduling problem, Computers and Operations Research, 35, 3202, 10.1016/j.cor.2007.02.014 Piramuthu, 2006, On preprocessing data for financial credit risk evaluation, Expert Systems with Applications, 30, 489, 10.1016/j.eswa.2005.10.006 Renner, 2003, Genetic algorithms in computer aided design, Computer-Aided Design, 35, 709, 10.1016/S0010-4485(03)00003-4 Šušteršic, 2009, Consumer credit scoring models with limited data, Expert Systems with Applications, 36, 4736, 10.1016/j.eswa.2008.06.016 Tsai, 2009, The consumer loan default predicting model – an application of DEA–DA and neural network, Expert Systems with Applications, 36, 11682, 10.1016/j.eswa.2009.03.009 Wang, 2009, Empirical analysis of support vector machine ensemble classifiers, Expert Systems with Applications, 36, 6466, 10.1016/j.eswa.2008.07.041 Yang, 2011, An improved genetic algorithm for optimal feature subset selection from multi-character feature set, Expert Systems with Applications, 38, 2733, 10.1016/j.eswa.2010.08.063 Zhang, 2011, An effective genetic algorithm for the flexible job-shop scheduling problem, Expert Systems with Applications, 38, 3563, 10.1016/j.eswa.2010.08.145