Feature selection in corporate credit rating prediction

Knowledge-Based Systems

Volumn 51, Issue , 2013, Pages 72-84

  Hajek, Petr ^a   Michalak, Krzysztof ^b  

^a UNIVERSITY OF PARDUBICE   (Czech Republic)

^b WROCLAW UNIVERSITY OF ECONOMICS   (Poland)

Author keywords

Classification; Credit rating; Feature selection; Mixed feature selection method; Wrapper

Indexed keywords

AUTOMATIC CLASSIFICATION; CLASSIFICATION PERFORMANCE; COMPUTATIONAL TIME; CORPORATE CREDIT RATINGS; CREDIT RATINGS; FEATURE SELECTION METHODS; SUPERVISED MACHINE LEARNING; WRAPPER;

CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; INDUSTRY;

RATING;

EID: 84883050191     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2013.07.008     Document Type: Article

References (73)

1. H. Ahn, K.J. Kim, Combining pairwise SVM classifiers for bond rating, in: KMIS International Conference, 2005, pp. 586-590.
2. H. Ahn, and K.J. Kim Corporate credit rating using multiclass classification models with order information World Academy of Science, Engineering and Technology 60 2011 95 100
3. E.I. Altman, H.A. Rijken, The Effects of Rating Through the Cycle on Rating Stability, Rating Timeliness and Default Prediction Performance, Working paper, 2005.
4. J.K. Bae, and J. Kim Combining models from neural networks and inductive learning algorithms Expert Systems with Applications 38 5 2011 4839 4850
5. A. Brabazon, and M. O'Neill Credit classification using grammatical evolution Informatica (Ljubljana) 30 3 2006 325 335
6. D. Brennan, and A. Brabazon Corporate bond rating using neural networks International Conference on Artificial Intelligence IC-AI'04 1 2004 161 167
7. E. Candes, and T. Tao The Dantzig selector: statistical estimation when p is much larger than n (with discussion) Annals of Statistics 35 6 2007 2313 2404
8. L. Cao, L.K. Guan, and Z. Jingquing Bond rating using support vector machine Intelligent Data Analysis 10 3 2006 285 296
9. Y. Chen, D. Miao, and R. Wang A rough set approach to feature selection based on ant colony optimization Pattern Recognition Letters 31 3 2010 226 233
10. D.Y. Choi, K.C. Lee, and N.Y. Jo Approach to corporate credit grading prediction using Bayesian Network model Information 14 9 2011 3143 3153
11. J. Cornaggia, K.J. Cornaggia, Does the Bond Market Want Informative Credit Ratings? Working paper, 2011.
12. S. Das, Filters, wrappers and a boosting-based hybrid for feature selection, in: The 18th International Conference on Machine Learning, 2001, pp. 74-81.
13. A. Delahunty, and D. OCallaghan Artificial Immune Systems for the Prediction of Corporate Failure and Classification of Corporate Bond Ratings 2004 University College Dublin Dublin
14. K. Dunne, P. Cunningham, F. Azuaje, Solutions to Instability Problems with Sequential Wrapper-Based Approaches to Feature Selection, Technical Report TCD-CD-2002-28, Department of Computer Science Courses, Trinity College, Dublin, 2002.
15. M.E. ElAlami A filter model for feature subset selection based on genetic algorithm Knowledge-Based Systems 22 5 2009 356 362
16. P.A. Estévez, M. Tesmer, C.A. Perez, and J.M. Zurada Normalized mutual information feature selection IEEE Transactions on Neural Networks 20 2 2009 189 201
17. J. Fan, and J. Lv Sure independence screening for ultra-high dimensional feature space (with discussion) Journal of Royal Statistical Society, Series B 70 2008 849 911
18. J. Fan, R. Samworth, and Y. Wu Ultrahigh dimensional feature selection: Beyond the linear model Journal of Machine Learning Research 10 2009 2013 2038
19. F. Fei, A.M. Fuertes, and E. Kalotychou Credit rating migration risk and business cycles Journal of Business Finance and Accounting 39 1-2 2012 229 263
20. N. Gaillard The determinants of Moody's sub-sovereign ratings International Research Journal of Finance and Economics 31 1 2009 194 209
21. A.P.M. Gama, and H.S.A. Geraldes Credit risk assessment and the impact of the New Basel Capital Accord on small and medium-sized enterprises: an empirical analysis Management Research Review 35 8 2012 727 749
22. I.A. Gheyas, and L.S. Smith Feature subset selection in large dimensionality domains Pattern Recognition 43 1 2010 5 13
23. X. Guo, Z. Zhu, and J. Shi A corporate credit rating model using support vector domain combined with fuzzy clustering algorithm Mathematical Problems in Engineering 2012 1 20
24. I. Guyon, and A. Elisseeff An introduction to variable and feature selection Journal of Machine Learning Research 3 2003 1157 1182
25. P. Hajek Credit Rating Modelling by Neural Networks 2010 Nova Science New York
26. P. Hajek, Probabilistic neural networks for credit rating modelling, in: Proceedings of the International Conference on Fuzzy Computation and International Conference on Neural Computing, vol. 1, Valencia, 2010, pp. 289-294.
27. P. Hajek Municipal credit rating modelling by neural networks Decision Support Systems 51 1 2011 108 118
28. P. Hajek Credit rating analysis using adaptive fuzzy rule-based systems: an industry-specific approach Central European Journal of Operations Research 20 3 2012 421 434
29. P. Hajek, and V. Olej Credit rating modelling by kernel-based approaches with supervised and semi-supervised learning Neural Computing & Applications 20 6 2011 761 773
30. M.A. Hall Correlation-Based Feature Subset Selection for Machine Learning 1998 Universtiy of Waikato Hamilton
31. A. Harol, C. Lai, E. Pekalska, and R.P.W. Duin Pairwise feature evaluation for constructing reduced representations Pattern Analysis and Applications 10 1 2007 55 68
32. Z. Huang, H. Chen, C.J. Hsu, W.H. Chen, and S. Wu Credit rating analysis with support vector machines and neural networks: a market comparative study Decision Support Systems 37 4 2004 543 558
33. J. Hua, W.D. Tembe, and E.R. Dougherty Performance of feature-selection methods in the classification of high-dimension data Pattern Recognition 42 3 2009 409 424
34. Ch.-L. Huang, and Ch.-J. Wang A GA-based feature selection and parameters optimization for support vector machines Expert Systems with Applications 31 2 2006 231 240
35. S.Ch. Huang Integrating nonlinear graph based dimensionality reduction schemes with SVM for credit rating forecasting Expert Systems with Applications 36 4 2009 7515 7518
36. R.C. Hwang, K.F. Cheng, and C.F. Lee On multiple-class prediction of issuer credit ratings Applied Stochastic Models in Business and Industry 25 5 2009 535 550
37. R.C. Hwang, H. Chung, and C.K. Chu Predicting issuer credit ratings using a semiparametric method Journal of Empirical Finance 17 1 2010 120 137
38. R.C. Hwang, Forecasting credit ratings with the varying-coefficient model, Quantitative Finance (ahead-of-print) (2013) 1-19.
39. R. Jensen, and Q. Shen New approaches to fuzzy-rough feature selection IEEE Transactions on Fuzzy Systems 17 4 2009 824 838
40. G.H. John, R. Kohavi, and K. Pfleger Irrelevant features and the subset selection problem W.W. Cohen, H. Hirsh, Machine Learning 1994 Morgan Kauffman vol. 129, pp. 121-129.
41. S.S. Kamar, and N. Ramaraj A novel hybrid feature selection via symmetrical uncertainty ranking based local memetic search algorithm Knowledge-Based Systems 23 6 2010 580 585
42. K. Kim, and H. Ahn A corporate credit rating model using multi-class support vector machines with an ordinal pairwise partitioning approach Computers & Operations Research 39 8 2012 1800 1811
43. K.S. Kim, and I. Han The cluster-indexing method for case-based reasoning using self-organizing maps and learning vector quantization for bond rating cases Expert Systems with Applications 21 3 2001 147 156
44. K.S. Kim Predicting bond ratings using publicly available information Expert Systems with Applications 29 1 2005 75 81
45. J. Kittler Feature set search algorithms C.H. Chen, Pattern Recognition and Signal Processing 1978 Sijthoff and Noordhoff Alphen aan den Rijn 41 60
46. R. Kohavi, and G. John Wrappers for feature subset selection Artificial Intelligence 97 12 1997 273 324
47. Y.C. Lee Application of support vector machines to corporate credit rating prediction Expert Systems with Applications 33 1 2007 67 74
48. J. Leng, C. Valli, L. Armstrong, A wrapper-based feature selection for analysis of large data sets, in: Proceedings of the 3rd International Conference on Computer and Electrical Engineering (ICCEE 2010), 2010, pp. 167-170.
49. H. Liu, R. Setiono, A probabilistic approach to feature selection - a filter solution, in: Proceedings of the 13th International Conference on Machine Learning ICML'1996, Bari, 1996, pp. 319-327.
50. O. Ludwig, and U. Nunes Novel maximum-margin training algorithms for supervised neural networks IEEE Transactions on Neural Networks 21 6 2010 972 984
51. M. Macas, L. Lhotska, E. Bakstein, D. Novak, J. Wild, T. Sieger, P. Vostatek, and R. Jech Wrapper feature selection for small sample size data driven by complete error estimates Computer Methods and Programs in Biomedicine 108 1 2012 138 150
52. S. Maldonado, and R. Weber A wrapper method for feature selection using support vector machines Information Science 179 13 2009 2208 2217
53. S. Maldonado, R. Weber, and J. Basak Simultaneous feature selection and classification using kernel-penalized support vector machines Information Sciences 181 1 2011 115 128
54. D. Martens, T. Van Gestel, M. De Backer, R. Haesen, J. Vanthienen, and B. Baesens Credit rating prediction using ant colony optimization Journal of the Operational Research Society 61 4 2009 561 573
55. K. Michalak, and H. Kwasnicka Correlation-based feature selection strategy in classification problems International Journal of Applied Mathematics and Computer Science 16 4 2006 503 511
56. K. Michalak, and H. Kwasnicka Correlation based feature selection method International Journal of Bio-Inspired Computation 2 5 2010 319 332
57. P. Mizen, and S. Tsoukas Forecasting US bond default ratings allowing for previous and initial state dependence in an ordered probit model International Journal of Forecasting 28 1 2012 273 287
58. H. Ogut, H.M. Doganay, N.B. Ceylan, and R. Aktas Prediction of bank financial strength ratings: the case of Turkey Economic Modelling 29 3 2012 632 640
59. A.L.I. Oliveira, P.L. Braga, R.M.F. Lima, and M.L. Cornelio GA-based method for feature selection and parameters optimization for machine learning regression applied to software effort estimation Information and Software Technology 52 11 2010 1155 1166
60. W. Orth The predictive accuracy of credit ratings: measurement and statistical inference International Journal of Forecasting 28 1 2012 288 329
61. E. Pekalska, A. Harol, C. Lai, R.P.W. Duin, Pairwise selection of features and prototypes, in: Proceedings of 4th International Conference on Computer Recognition Systems CORES'05, Advances in Soft Computing, Springer, 2005, pp. 271-278.
62. J. Platt Fast training of support vector machines using sequential minimal optimization Advances in Kernel Methods - Support Vector Learning 1999 MIT Press pp. 185-208.
63. N. Sánchez-Marono, A. Alonso-Betanzos, M. Tombilla- Sanromán, Filter methods for feature selection - a comparative study, in: H. Yin, P. Tino, E. Corchado, W.M. Byrne, X. Yao (Eds.), Intelligent Data Engineering and Automated Learning - IDEAL 2007, Lecture Notes in Computer Science, vol. 4881, 2007, pp. 178-187.
64. Ch.H. Shen, Y.L. Huang, I. Hasan, Assymetric Benchmarking in Bank Credit Rating, Bank of Finland Research Discussion Papers 13, 2012.
65. K.S. Shin, and I. Han A case-based approach using inductive indexing for corporate bond rating Decisions Support Systems 32 1 2001 41 52
66. R. Tibshirani, T. Hastie, B. Narasimhan, and G. Chu Class prediction by nearest shrunken centroids, with applications to DNA microarrays Statistical Science 18 1 2003 104 117
67. L.I. Tong, Ch.H. Yang, H.P. Yu, Credit rating analysis using general regression neural network, in: Proceedings of the 2nd International Conference on Innovations of Management and Interdisciplinary, 2005, pp. 1-11.
68. Ch.F. Tsai Feature selection in bankruptcy prediction Knowledge-Based Systems 22 2009 120 127
69. E. Tuv, A. Borisov, G. Runger, and K. Torkkola Feature selection with ensembles, artificial variables, and redundancy elimination Journal of Machine Learning Research 10 2009 1341 1366
70. L.D. Vignolo, D.H. Milone, J. Scharcanski, C. Behaine, An evolutionary wrapper for feature selection in face recognition applications, in: Proceedings of the 2012 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2012), 2012, pp. 1286-1290.
71. Ch.Ch. Yeh, F. Lin, and Ch.Y. Hsu A hybrid KMV model, random forests and rough set theory approach for credit rating Knowledge-Based Systems 33 2012 166 172
72. P. Wijayatunga, S. Mase, and M. Nakamura Appraisal of companies with Bayesian networks International Journal of Business Intelligence and Data Mining 1 3 2006 329 346
73. B.K. Wong, V.S. Lai, and J. Lam A bibliography of neural network business applications research: 1994-1998 Computers and Operations Research 27 11-12 2000 1045 1076