{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T12:47:24Z","timestamp":1774529244914,"version":"3.50.1"},"reference-count":129,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2015,10,27]],"date-time":"2015-10-27T00:00:00Z","timestamp":1445904000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["91024004"],"award-info":[{"award-number":["91024004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"published-print":{"date-parts":[[2016,1]]},"DOI":"10.1007\/s10462-015-9434-x","type":"journal-article","created":{"date-parts":[[2015,10,27]],"date-time":"2015-10-27T19:46:58Z","timestamp":1445975218000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":166,"title":["Financial credit risk assessment: a recent review"],"prefix":"10.1007","volume":"45","author":[{"given":"Ning","family":"Chen","sequence":"first","affiliation":[]},{"given":"Bernardete","family":"Ribeiro","sequence":"additional","affiliation":[]},{"given":"An","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,10,27]]},"reference":[{"key":"9434_CR1","unstructured":"Alaiz-Rodriguez R, Japkowicz N, Tischer P (2008) A visualization-based exploratory tool for classifier comparison with respect to multiple metrics and multiple domains. In: Proceedings of ECML PKDD, pp 660\u2013665"},{"issue":"4","key":"9434_CR2","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1111\/j.1540-6261.1968.tb00843.x","volume":"23","author":"EI Altman","year":"1968","unstructured":"Altman EI (1968) Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J Finance 23(4):589\u2013609","journal-title":"J Finance"},{"issue":"10","key":"9434_CR3","doi-asserted-by":"crossref","first-page":"9159","DOI":"10.1016\/j.eswa.2012.02.058","volume":"39","author":"JK Bae","year":"2012","unstructured":"Bae JK (2012) Predicting financial distress of the South Korean manufacturing industries. Expert Syst Appl 39(10):9159\u20139165","journal-title":"Expert Syst Appl"},{"issue":"1","key":"9434_CR4","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.bar.2005.09.001","volume":"38","author":"S Balcaen","year":"2006","unstructured":"Balcaen S, Ooghe H (2006) 35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems. Br Account Rev 38(1):63\u201393","journal-title":"Br Account Rev"},{"key":"9434_CR5","first-page":"1","volume":"33","author":"J Bellovary","year":"2007","unstructured":"Bellovary J, Giacomino D, Akers M (2007) A review of bankruptcy prediction studies: 1930 to present. J Financ Educ 33:1\u201343","journal-title":"J Financ Educ"},{"issue":"1","key":"9434_CR6","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1016\/j.eswa.2012.07.051","volume":"40","author":"A Blanco","year":"2013","unstructured":"Blanco A, Pino-Mejias R, Lara J, Rayo S (2013) Credit scoring models for the microfinance industry using neural networks: evidence from Peru. Expert Syst Appl 40(1):356\u2013364","journal-title":"Expert Syst Appl"},{"key":"9434_CR7","doi-asserted-by":"crossref","first-page":"1707","DOI":"10.1007\/978-3-540-92910-9_51","volume-title":"Handbook of natural computing","author":"A Brabazon","year":"2012","unstructured":"Brabazon A, Dang J, Dempsey I, O\u2019Neill M, Edelman D (2012) Natural computing in finance: a review. In: Rozenberg G, Back T, Kok J (eds) Handbook of natural computing. Springer, Berlin, pp 1707\u20131735"},{"key":"9434_CR8","volume-title":"Classification and regression trees","author":"L Breiman","year":"1984","unstructured":"Breiman L, Friedman J, Olshen R, Stone C (1984) Classification and regression trees. Wadsworth, Belmont, CA"},{"key":"9434_CR9","unstructured":"Brezigar-Masten A, Masten I (2009) Comparison of parametric, semi-parametric and non-parametric methods in bankruptcy prediction. IMAD Working Paper Series XVIII, vol 18"},{"issue":"11","key":"9434_CR10","doi-asserted-by":"crossref","first-page":"10153","DOI":"10.1016\/j.eswa.2012.02.125","volume":"39","author":"A Brezigar-Masten","year":"2012","unstructured":"Brezigar-Masten A, Masten I (2012) CART-based selection of bankruptcy predictors for the logit model. Expert Syst Appl 39(11):10153\u201310159","journal-title":"Expert Syst Appl"},{"issue":"4","key":"9434_CR11","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/S1467-0895(02)00068-4","volume":"3","author":"TG Calderon","year":"2002","unstructured":"Calderon TG, Cheh JJ (2002) A roadmap for future neural networks research in auditing and risk assessment. Int J Account Inf Syst 3(4):203\u2013236","journal-title":"Int J Account Inf Syst"},{"key":"9434_CR12","doi-asserted-by":"crossref","unstructured":"Canuto AM, Abreu MC, Oliveira LM Jr, Xavier JC, Santos AM (2007) Investigating the influence of the choice of the ensemble members in accuracy and diversity of selection-based and fusion-based methods for ensembles. Pattern Recognit Lett 28(4):472\u2013486","DOI":"10.1016\/j.patrec.2006.09.001"},{"key":"9434_CR13","doi-asserted-by":"crossref","unstructured":"Caruana R, Niculescu-Mizil A (2004) Data mining in metric space: an empirical analysis of suppervised learning performance criteria. In: Proceedings of the 10th international conference on knowledge discovery and data mining","DOI":"10.1145\/1014052.1014063"},{"issue":"4","key":"9434_CR14","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1504\/IJEF.2007.012898","volume":"1","author":"S Chakraborty","year":"2007","unstructured":"Chakraborty S, Sharma SK (2007) Prediction of corporate financial health by artificial neural network. Int J Electron Finance 1(4):442\u2013459","journal-title":"Int J Electron Finance"},{"key":"9434_CR15","first-page":"303","volume":"5","author":"C Charalambous","year":"2000","unstructured":"Charalambous C, Charitou A, Kaourou F (2000) Application of feature extractive algorithm to bankruptcy prediction. Int Jt Conf Neural Netw 5:303\u2013308","journal-title":"Int Jt Conf Neural Netw"},{"key":"9434_CR16","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1007\/978-3-642-38577-3_54","volume-title":"Recent trends in applied artificial intelligence, LNCS","author":"MY Chen","year":"2013","unstructured":"Chen MY, Chen CC, Liu JY (2013) Credit rating analysis with support vector machines and artificial bee colony algorithm. In: Ali M, Bosse T, Hindriks K, Hoogendoorn M, Jonker CM, Treur J (eds) Recent trends in applied artificial intelligence, LNCS, vol 7906. Springer, Berlin, pp 528\u2013534"},{"issue":"3","key":"9434_CR17","doi-asserted-by":"crossref","first-page":"423","DOI":"10.3233\/IDA-130587","volume":"17","author":"N Chen","year":"2013","unstructured":"Chen N, Chen A, Ribeiro B (2013) Influence of class distribution on cost-sensitive learning: a case study of french bankruptcy analysis. Int J Intell Data Anal 17(3):423\u2013437","journal-title":"Int J Intell Data Anal"},{"key":"9434_CR18","doi-asserted-by":"crossref","unstructured":"Chen N, Ribeiro B (2013) A consensus approach for combining multiple classifiers in cost-sensitive bankruptcy prediction. In: M.T. et\u00a0al (ed.) 11th international conference on adaptive and natural computing algorithms (ICANNGA\u201913), LNCS, vol 7824. Springer, Berlin, pp 266\u2013276","DOI":"10.1007\/978-3-642-37213-1_28"},{"issue":"1","key":"9434_CR19","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1016\/j.eswa.2012.07.047","volume":"40","author":"N Chen","year":"2013","unstructured":"Chen N, Ribeiro B, Vieira A, Chen A (2013) Clustering and visualization of bankruptcy trajectory using self-organizing map. Expert Syst Appl 40(1):385\u2013393","journal-title":"Expert Syst Appl"},{"issue":"10","key":"9434_CR20","doi-asserted-by":"crossref","first-page":"12939","DOI":"10.1016\/j.eswa.2011.04.090","volume":"38","author":"N Chen","year":"2011","unstructured":"Chen N, Ribeiro B, Vieira A, Duarte J, Neves J (2011) A genetic algorithm-based approach to cost-sensitive bankruptcy prediction. Expert Syst Appl 38(10):12939\u201312945","journal-title":"Expert Syst Appl"},{"key":"9434_CR21","unstructured":"Chen N, Vieira A (2009) Bankruptcy prediction based on independent component analysis. In: 1st international conference on agents and artificial intelligence (ICAART09). pp 150\u2013155"},{"key":"9434_CR22","doi-asserted-by":"crossref","unstructured":"Chen N, Vieira A, Duarte J, Ribeiro B, Neves J (2009) Cost-sensitive learning vector quantization for financial distress prediction. In: Lecture notes in artificial intelligence (LNAI 5816). Springer, Berlin, pp 374\u2013385","DOI":"10.1007\/978-3-642-04686-5_31"},{"issue":"2","key":"9434_CR23","doi-asserted-by":"crossref","first-page":"237","DOI":"10.3233\/IDA-2010-0465","volume":"15","author":"N Chen","year":"2011","unstructured":"Chen N, Vieira A, Ribeiro B, Duarte J, Neves J (2011) A stable credit rating model based on learning vector quantization. Intell Data Anal 15(2):237\u2013250","journal-title":"Intell Data Anal"},{"issue":"9","key":"9434_CR24","doi-asserted-by":"crossref","first-page":"1055","DOI":"10.1080\/14697680902814274","volume":"10","author":"KF Cheng","year":"2010","unstructured":"Cheng KF, Chu CK, Hwang R (2010) Predicting bankruptcy using the discrete-time semi-parametric hazard model. Quant Finance 10(9):1055\u20131066","journal-title":"Quant Finance"},{"key":"9434_CR25","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.ins.2013.02.015","volume":"236","author":"CL Chuang","year":"2013","unstructured":"Chuang CL (2013) Application of hybrid case-based reasoning for enhanced performance in bankruptcy prediction. Inf Sci 236:174\u2013185","journal-title":"Inf Sci"},{"key":"9434_CR26","unstructured":"Coface, for Safer Trade (2012) Risk assessment of Portugal. http:\/\/www.coface.com\/Economic-Studies-and-Country-Risks\/Portugal"},{"issue":"3","key":"9434_CR27","doi-asserted-by":"crossref","first-page":"1447","DOI":"10.1016\/j.ejor.2006.09.100","volume":"183","author":"JN Crook","year":"2007","unstructured":"Crook JN, Edelman DB, Thomas LC (2007) Recent developments in consumer credit risk assessment. Eur J Oper Res 183(3):1447\u20131465","journal-title":"Eur J Oper Res"},{"issue":"10","key":"9434_CR28","doi-asserted-by":"crossref","first-page":"3970","DOI":"10.1016\/j.eswa.2013.01.012","volume":"40","author":"D Delen","year":"2013","unstructured":"Delen D, Kuzey C, Uyar A (2013) Measuring firm performance using financial ratios: a decision tree approach. Expert Syst Appl 40(10):3970\u20133983","journal-title":"Expert Syst Appl"},{"key":"9434_CR29","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/978-3-642-30448-4_9","volume-title":"Artificial intelligence: theories and applications, LNCS","author":"D Deligianni","year":"2012","unstructured":"Deligianni D, Kotsiantis S (2012) Forecasting corporate bankruptcy with an ensemble of classifiers. In: Maglogiannis I, Plagianakos V, Vlahavas I (eds) Artificial intelligence: theories and applications, LNCS, vol 7297. Springer, Berlin, pp 65\u201372"},{"key":"9434_CR30","first-page":"1","volume":"7","author":"J Demsar","year":"2006","unstructured":"Demsar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7:1\u201330","journal-title":"J Mach Learn Res"},{"issue":"3","key":"9434_CR31","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1016\/0377-2217(95)00070-4","volume":"90","author":"A Dimitras","year":"1996","unstructured":"Dimitras A, Zanakis S, Zopounidis C (1996) A survey of business failures with an emphasis on prediction methods and industrial applications. Eur J Oper Res 90(3):487\u2013513","journal-title":"Eur J Oper Res"},{"key":"9434_CR32","doi-asserted-by":"crossref","unstructured":"Domingos P (1999) Metacost: a general method for making classifiers cost-sensitive. In: Proceedings of 5th ACM SIGKDD international conference on knowledge discovery and data mining. pp 155\u2013164","DOI":"10.1145\/312129.312220"},{"key":"9434_CR33","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1021\/ci6002619","volume":"47","author":"T Eitrich","year":"2007","unstructured":"Eitrich T, Kless A, Druska C, Meyer W, Grotendorst J (2007) Classification of highly unbalanced CYP450 data of drugs using cost sensitive machine learning techniques. J Chem Inf Model 47:92\u2013103","journal-title":"J Chem Inf Model"},{"issue":"7","key":"9434_CR34","doi-asserted-by":"crossref","first-page":"1689","DOI":"10.1016\/j.engappai.2013.03.014","volume":"26","author":"HI Erdal","year":"2013","unstructured":"Erdal HI (2013) Two-level and hybrid ensembles of decision trees for high performance concrete compressive strength prediction. Eng Appl Artif Intell 26(7):1689\u20131697","journal-title":"Eng Appl Artif Intell"},{"key":"9434_CR35","doi-asserted-by":"crossref","unstructured":"Esfandiary N, Azad I, Eftekhari Moghadam AM (2013) Ldt: layered decision tree based on data clustering. In: Proceedings of the 13th Iranian conference on fuzzy systems (IFSC). pp 1\u20134","DOI":"10.1109\/IFSC.2013.6675584"},{"issue":"2","key":"9434_CR36","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1016\/j.ejor.2010.09.029","volume":"210","author":"S Finlay","year":"2011","unstructured":"Finlay S (2011) Multiple classifier architectures and their application to credit risk assessment. Eur J Oper Res 210(2):368\u2013378","journal-title":"Eur J Oper Res"},{"key":"9434_CR37","first-page":"598","volume":"10","author":"PJ FitzPatrick","year":"1932","unstructured":"FitzPatrick PJ (1932) A comparison of the ratios of successful industrial enterprises with those of failed companies. J Account Res 10:598\u2013605","journal-title":"J Account Res"},{"key":"9434_CR38","unstructured":"Frank A, Asuncion A (2010) UCI machine learning repository. http:\/\/archive.ics.uci.edu\/ml"},{"key":"9434_CR39","unstructured":"Fu-yuan H (2008) A genetic fuzzy neural network for bankruptcy prediction in chinese corporations. In: International conference on risk management and engineering management (ICRMEM \u201908). pp 542\u2013546"},{"issue":"10","key":"9434_CR40","doi-asserted-by":"crossref","first-page":"2044","DOI":"10.1016\/j.ins.2009.12.010","volume":"180","author":"S Garcia","year":"2010","unstructured":"Garcia S, Fernandez A, Luengo J, Herrera F (2010) Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power. Inf Sci 180(10):2044\u20132064","journal-title":"Inf Sci"},{"key":"9434_CR41","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.knosys.2011.06.013","volume":"25","author":"V Garc\u00eda","year":"2012","unstructured":"Garc\u00eda V, S\u00e1nchez JS, Mollineda RA (2012) On the effectiveness of preprocessing methods when dealing with different levels of class imbalance. Knowl Based Syst 25:13\u201321","journal-title":"Knowl Based Syst"},{"issue":"3","key":"9434_CR42","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1111\/j.1467-985X.1997.00078.x","volume":"160","author":"DJ Hand","year":"1997","unstructured":"Hand DJ, Henley WE (1997) Statistical classification methods in consumer credit scoring: a review. J R Stat Soc Ser A (Stat Soc) 160(3):523\u2013541","journal-title":"J R Stat Soc Ser A (Stat Soc)"},{"key":"9434_CR43","unstructured":"Hansen PR, Timmermann A (2012) Choice of sample split in out-of-sample forecast evaluation. Economics Working Papers ECO2012\/10"},{"issue":"4","key":"9434_CR44","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1016\/S0167-9236(03)00086-1","volume":"37","author":"Z Huang","year":"2004","unstructured":"Huang Z, Chen H, Hsu CJ, Chen WH, Wu S (2004) Credit rating analysis with support vector machines and neural networks: a market comparative study. Decis Support Syst 37(4):543\u2013558","journal-title":"Decis Support Syst"},{"issue":"3, Part 1","key":"9434_CR45","doi-asserted-by":"crossref","first-page":"5297","DOI":"10.1016\/j.eswa.2008.06.068","volume":"36","author":"C Hung","year":"2009","unstructured":"Hung C, Chen JH (2009) A selective ensemble based on expected probabilities for bankruptcy prediction. Expert Syst Appl 36(3, Part 1):5297\u20135303","journal-title":"Expert Syst Appl"},{"key":"9434_CR46","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1002\/for.1027","volume":"26","author":"R Hwang","year":"2007","unstructured":"Hwang R, Cheng KF, Lee J (2007) A semi-parametric method for predicting bankruptcy. J Forecast 26:317\u2013342","journal-title":"J Forecast"},{"issue":"1","key":"9434_CR47","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.jempfin.2009.07.007","volume":"17","author":"R Hwang","year":"2010","unstructured":"Hwang R, Ruey-Ching, Chung H, Chu C (2010) Predicting issuer credit ratings using a semi-parametric method. J Empir Finance 17(1):120\u2013137","journal-title":"J Empir Finance"},{"issue":"3","key":"9434_CR48","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1145\/331499.331504","volume":"31","author":"AK Jain","year":"1999","unstructured":"Jain AK, Murty MN, Flynn PJ (1999) Data clustering: a review. ACM Comput Surv 31(3):264\u2013323","journal-title":"ACM Comput Surv"},{"key":"9434_CR49","doi-asserted-by":"crossref","unstructured":"Japkowicz N, Sanghi P, Tischer P (2008) A projection-based framework for classifier performance evaluation. In: Proceedings of European conference on machine learning and knowledge discovery in databases-part 1, vol 5211. LNCS Springer, Heidelberg, pp 548\u2013563","DOI":"10.1007\/978-3-540-87479-9_54"},{"issue":"7","key":"9434_CR50","first-page":"39","volume":"33","author":"J Jayanthi","year":"2011","unstructured":"Jayanthi J, Joseph KS, Vaishnavi J (2011) Bankruptcy prediction using SVM and hybrid SVM survey. Int J Comput Appl 33(7):39\u201345","journal-title":"Int J Comput Appl"},{"issue":"2","key":"9434_CR51","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/S0957-4174(97)00011-0","volume":"13","author":"H Jo","year":"1997","unstructured":"Jo H, Han I, Lee H (1997) Bankruptcy prediction using case-based reasoning, neural networks, and discriminant analysis. Expert Syst Appl 13(2):97\u2013108","journal-title":"Expert Syst Appl"},{"issue":"17","key":"9434_CR52","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1186\/1472-6947-11-51","volume":"11","author":"M Khalilia","year":"2011","unstructured":"Khalilia M, Chakrabort S, Popescu M (2011) Predicting disease risks from highly imbalanced data using random forest. BMC Med Inform Decis Mak 11(17):51","journal-title":"BMC Med Inform Decis Mak"},{"issue":"10","key":"9434_CR53","doi-asserted-by":"crossref","first-page":"9308","DOI":"10.1016\/j.eswa.2012.02.072","volume":"39","author":"MJ Kim","year":"2012","unstructured":"Kim MJ, Kang DK (2012) Classifiers selection in ensembles using genetic algorithms for bankruptcy prediction. Expert Syst Appl 39(10):9308\u20139314","journal-title":"Expert Syst Appl"},{"issue":"2","key":"9434_CR54","doi-asserted-by":"crossref","first-page":"387","DOI":"10.2307\/2951556","volume":"61","author":"RW Klein","year":"1993","unstructured":"Klein RW, Spady RH (1993) An efficient semiparametric estimator for binary response models. Econometrica 61(2):387\u2013421","journal-title":"Econometrica"},{"key":"9434_CR55","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.econmod.2012.11.017","volume":"31","author":"T Korol","year":"2013","unstructured":"Korol T (2013) Early warning models against bankruptcy risk for central european and latin american enterprises. Econ Model 31:22\u201330","journal-title":"Econ Model"},{"key":"9434_CR56","first-page":"26","volume":"14","author":"M Kouki","year":"2011","unstructured":"Kouki M, Elkhaldi A (2011) Toward a predicting model of firm bankruptcy: evidence from the Tunisian context. Middle East Finance Econ 14:26\u201343","journal-title":"Middle East Finance Econ"},{"key":"9434_CR57","doi-asserted-by":"crossref","DOI":"10.1002\/0471660264","volume-title":"Combining pattern classifiers","author":"LI Kuncheva","year":"2004","unstructured":"Kuncheva LI (2004) Combining pattern classifiers. Wiley, New York"},{"issue":"2","key":"9434_CR58","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1023\/A:1022859003006","volume":"51","author":"LI Kuncheva","year":"2003","unstructured":"Kuncheva LI, Whitaker CJ (2003) Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy. Mach Learn 51(2):181\u2013207","journal-title":"Mach Learn"},{"issue":"4","key":"9434_CR59","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1007\/s11156-011-0238-z","volume":"38","author":"W Kwak","year":"2012","unstructured":"Kwak W, Shi Y, Kou G (2012) Bankruptcy prediction for Korean firms after the 1997 financial crisis: using a multiple criteria linear programming data mining approach. Rev Quant Finance Account 38(4):441\u2013453","journal-title":"Rev Quant Finance Account"},{"key":"9434_CR60","doi-asserted-by":"crossref","unstructured":"Lam M, Trinkle BS (2014) Using prediction intervals to improve information quality of bankruptcy prediction models, chap. 8, pp 37\u201352","DOI":"10.1108\/S1477-407020140000010014"},{"issue":"2","key":"9434_CR61","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1016\/j.cor.2010.06.008","volume":"38","author":"H Li","year":"2011","unstructured":"Li H, Adeli H, Sun J, Han JG (2011) Hybridizing principles of TOPSIS with case-based reasoning for business failure prediction. Comput Oper Res 38(2):409\u2013419","journal-title":"Comput Oper Res"},{"issue":"5","key":"9434_CR62","doi-asserted-by":"crossref","first-page":"6244","DOI":"10.1016\/j.eswa.2010.11.043","volume":"38","author":"H Li","year":"2011","unstructured":"Li H, Sun J (2011) Empirical research of hybridizing principal component analysis with multivariate discriminant analysis and logistic regression for business failure prediction. Expert Syst Appl 38(5):6244\u20136253","journal-title":"Expert Syst Appl"},{"issue":"6","key":"9434_CR63","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.im.2011.05.001","volume":"48","author":"H Li","year":"2011","unstructured":"Li H, Sun J (2011) Principal component case-based reasoning ensemble for business failure prediction. Inf Manage 48(6):220\u2013227","journal-title":"Inf Manage"},{"issue":"2","key":"9434_CR64","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1002\/for.1265","volume":"32","author":"H Li","year":"2013","unstructured":"Li H, Sun J (2013) Predicting business failure using an RSF-based case-based reasoning ensemble forecasting method. J Forecast 32(2):180\u2013192","journal-title":"J Forecast"},{"issue":"8","key":"9434_CR65","doi-asserted-by":"crossref","first-page":"5895","DOI":"10.1016\/j.eswa.2010.02.016","volume":"37","author":"H Li","year":"2010","unstructured":"Li H, Sun J, Wu J (2010) Predicting business failure using classification and regression tree: an empirical comparison with popular classical statistical methods and top classification mining methods. Expert Syst Appl 37(8):5895\u20135904","journal-title":"Expert Syst Appl"},{"issue":"5","key":"9434_CR66","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1007\/s11424-014-3273-8","volume":"27","author":"J Li","year":"2014","unstructured":"Li J, Pan L, Chen M, Yang X (2014) Parametric and non-parametric combination model to enhance overall performance on default prediction. J Syst Sci Complex 27(5):950\u2013969. doi: 10.1007\/s11424-014-3273-8","journal-title":"J Syst Sci Complex"},{"issue":"4","key":"9434_CR67","doi-asserted-by":"crossref","first-page":"818","DOI":"10.1016\/j.jempfin.2010.04.004","volume":"17","author":"MYL Li","year":"2010","unstructured":"Li MYL, Miu P (2010) A hybrid bankruptcy prediction model with dynamic loadings on accounting-ratio-based and market-based information. J Empir Finance 17(4):818\u2013833","journal-title":"J Empir Finance"},{"key":"9434_CR68","first-page":"82","volume":"1","author":"F Lin","year":"2013","unstructured":"Lin F, Yeh C, Lee M (2013) A hybrid business failure prediction model using locally linear embedding and support vector machines. Rom J Econ Forecast 1:82\u201397","journal-title":"Rom J Econ Forecast"},{"issue":"1","key":"9434_CR69","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.knosys.2010.07.009","volume":"24","author":"F Lin","year":"2011","unstructured":"Lin F, Yeh CC, Lee MY (2011) The use of hybrid manifold learning and support vector machines in the prediction of business failure. Knowl Based Syst 24(1):95\u2013101","journal-title":"Knowl Based Syst"},{"issue":"4","key":"9434_CR70","doi-asserted-by":"crossref","first-page":"1817","DOI":"10.1016\/j.eswa.2007.08.088","volume":"35","author":"SW Lin","year":"2008","unstructured":"Lin SW, Ying KC, Chen SC, Lee ZJ (2008) Particle swarm optimization for parameter determination and feature selection of support vector machines. Expert Syst Appl 35(4):1817\u20131824","journal-title":"Expert Syst Appl"},{"issue":"4","key":"9434_CR71","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1109\/TSMCC.2011.2170420","volume":"42","author":"WY Lin","year":"2012","unstructured":"Lin WY, Hu YH, Tsai CF (2012) Machine learning in financial crisis prediction: a survey. IEEE Trans Syst Man Cybern C Appl Rev 42(4):421\u2013436","journal-title":"IEEE Trans Syst Man Cybern C Appl Rev"},{"key":"9434_CR72","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1023\/A:1012406528296","volume":"46","author":"Y Lin","year":"2002","unstructured":"Lin Y, Lee Y, Wahba G (2002) Support vector machines for classification in nonstandard situations. Mach Learn 46:191\u2013202","journal-title":"Mach Learn"},{"key":"9434_CR73","doi-asserted-by":"crossref","unstructured":"Liu XY, Zhou Z (2006) The influence of class imbalance on cost-sensitive learning: An empirical study. In: Proceedings of 6th IEEE international conference on data mining (ICDM06). pp 970\u2013974","DOI":"10.1109\/ICDM.2006.158"},{"issue":"1\u20134","key":"9434_CR74","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s10462-009-9114-9","volume":"30","author":"AC Lorena","year":"2008","unstructured":"Lorena AC, Carvalho AC, Gama JM (2008) A review on the combination of binary classifiers in multiclass problems. Artif Intell Rev 30(1\u20134):19\u201337","journal-title":"Artif Intell Rev"},{"issue":"1\u20132","key":"9434_CR75","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1007\/s10994-013-5339-6","volume":"98","author":"A Lourenco","year":"2015","unstructured":"Lourenco A, Bulo SR, Rebagliati N, Fred ALN, Figueiredo MAT, Pelillo M (2015) Probabilistic consensus clustering using evidence accumulation. Mach Learn 98(1\u20132):331\u2013357","journal-title":"Mach Learn"},{"issue":"7","key":"9434_CR76","doi-asserted-by":"crossref","first-page":"10604","DOI":"10.1016\/j.eswa.2009.02.055","volume":"36","author":"Y Marinakis","year":"2009","unstructured":"Marinakis Y, Marinaki M, Doumpos M, Zopounidis C (2009) Ant colony and particle swarm optimization for financial classification problems. Expert Syst Appl 36(7):10604\u201310611","journal-title":"Expert Syst Appl"},{"issue":"12","key":"9434_CR77","doi-asserted-by":"crossref","first-page":"10916","DOI":"10.1016\/j.eswa.2012.03.033","volume":"39","author":"A Marqu\u00e9s","year":"2012","unstructured":"Marqu\u00e9s A, Garc\u00eda V, S\u00e1nchez J (2012) Two-level classifier ensembles for credit risk assessment. Expert Syst Appl 39(12):10916\u201310922","journal-title":"Expert Syst Appl"},{"issue":"1","key":"9434_CR78","first-page":"1","volume":"17","author":"JH Min","year":"2011","unstructured":"Min JH, Jeong C, Kim M (2011) Tuning the architecture of support vector machine: the case of bankruptcy prediction. Int J Manage Sci 17(1):1\u2013116","journal-title":"Int J Manage Sci"},{"issue":"4","key":"9434_CR79","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1016\/j.eswa.2004.12.008","volume":"28","author":"JH Min","year":"2005","unstructured":"Min JH, Lee YC (2005) Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters. Expert Syst Appl 28(4):603\u2013614","journal-title":"Expert Syst Appl"},{"key":"9434_CR80","unstructured":"Musehane R, Netshiongolwe F, Nelwamondo FV, Masisi L, Marwala T (2008) Relationship between diversity and perfomance of multiple classifiers for decision support. Comput Res Repos. abs\/0810.3"},{"issue":"2, Part 2","key":"9434_CR81","doi-asserted-by":"crossref","first-page":"3028","DOI":"10.1016\/j.eswa.2008.01.018","volume":"36","author":"L Nanni","year":"2009","unstructured":"Nanni L, Lumini A (2009) An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring. Expert Syst Appl 36(2, Part 2):3028\u20133033","journal-title":"Expert Syst Appl"},{"key":"9434_CR82","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.knosys.2013.03.001","volume":"47","author":"C Orsenigo","year":"2013","unstructured":"Orsenigo C, Vercellis C (2013) Linear versus nonlinear dimensionality reduction for banks credit rating prediction. Knowl Based Syst 47:14\u201322","journal-title":"Knowl Based Syst"},{"key":"9434_CR83","unstructured":"Pai GR, Annapoorani R, Pai GV (2004) Performance analysis of a statistical and an evolutionary neural network based classifier for the prediction of industrial bankruptcy. In: IEEE conference on cybernetics and intelligent systems. pp 1033\u20131038"},{"issue":"3","key":"9434_CR84","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/S0957-4174(02)00045-3","volume":"23","author":"CS Park","year":"2002","unstructured":"Park CS, Han I (2002) A case-based reasoning with the feature weights derived by analytic hierarchy process for bankruptcy prediction. Expert Syst Appl 23(3):255\u2013264","journal-title":"Expert Syst Appl"},{"key":"9434_CR85","doi-asserted-by":"crossref","first-page":"1456","DOI":"10.1016\/j.eswa.2007.01.011","volume":"34","author":"P Pendharkar","year":"2008","unstructured":"Pendharkar P (2008) A threshold varying bisection method for cost sensitive learning in neural networks. Expert Syst Appl 34:1456\u20131464","journal-title":"Expert Syst Appl"},{"key":"9434_CR86","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1007\/11428862_75","volume":"3516","author":"Y Peng","year":"2005","unstructured":"Peng Y, Kou G, Shi Y, Chen Z (2005) Improving clustering analysis for credit card accounts classification. Lect Notes Comput Sci 3516:548\u2013553","journal-title":"Lect Notes Comput Sci"},{"issue":"8","key":"9434_CR87","doi-asserted-by":"crossref","first-page":"10210","DOI":"10.1016\/j.eswa.2011.02.082","volume":"38","author":"FM Rafiei","year":"2011","unstructured":"Rafiei FM, Manzari S, Bostanian S (2011) Financial health prediction models using artificial neural networks, genetic algorithm and multivariate discriminant analysis: Iranian evidence. Expert Syst Appl 38(8):10210\u201310217","journal-title":"Expert Syst Appl"},{"issue":"1","key":"9434_CR88","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/j.asoc.2007.02.001","volume":"8","author":"V Ravi","year":"2008","unstructured":"Ravi V, Kurniawan H, Thai PNK, Kumar PR (2008) Soft computing system for bank performance prediction. Appl Soft Comput 8(1):305\u2013315","journal-title":"Appl Soft Comput"},{"issue":"1","key":"9434_CR89","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ejor.2006.08.043","volume":"180","author":"P Ravi Kumar","year":"2007","unstructured":"Ravi Kumar P, Ravi V (2007) Bankruptcy prediction in banks and firms via statistical and intelligent techniques: a review. Eur J Oper Res 180(1):1\u201328","journal-title":"Eur J Oper Res"},{"key":"9434_CR90","doi-asserted-by":"crossref","unstructured":"Ravikumar P, Ravi V (2006) Bankruptcy prediction in banks by an ensemble classifier. In: IEEE international conference on industrial technology. pp 2032\u20132036","DOI":"10.1109\/ICIT.2006.372529"},{"issue":"8","key":"9434_CR91","doi-asserted-by":"crossref","first-page":"1257","DOI":"10.1016\/j.ins.2009.12.022","volume":"180","author":"P Ravisankar","year":"2010","unstructured":"Ravisankar P, Ravi V, Bose I (2010) Failure prediction of dotcom companies using neural networkcgenetic programming hybrids. Inf Sci 180(8):1257\u20131267","journal-title":"Inf Sci"},{"key":"9434_CR92","doi-asserted-by":"crossref","unstructured":"Ribeiro B, Chen N (2011) Graph weighted subspace learning models in bankruptcy. In: Proceedings IEEE international joint conference on neural networks (IJCNN). pp 2055\u20132061","DOI":"10.1109\/IJCNN.2011.6033479"},{"key":"9434_CR93","doi-asserted-by":"crossref","unstructured":"Ribeiro B, Chen N (2012a) Biclustering and subspace learning with regularization for financial risk analysis. In: Proceedings of international conference on neural information processing, part II, LNCS, vol 7664. pp 616\u2013623","DOI":"10.1007\/978-3-642-34487-9_28"},{"key":"9434_CR94","doi-asserted-by":"crossref","unstructured":"Ribeiro B, Chen N (2012b) Biclustering and subspace learning with regularization for financial risk analysis. In: T.H. et\u00a0al. (ed.) Proceedings of the 19th international conference on neural information processing (ICONIP), part III, LNCS, vol 7665. Springer, Berlin, pp 228\u2013235","DOI":"10.1007\/978-3-642-34487-9_28"},{"key":"9434_CR95","doi-asserted-by":"crossref","first-page":"10140","DOI":"10.1016\/j.eswa.2012.02.142","volume":"39","author":"B Ribeiro","year":"2012","unstructured":"Ribeiro B, Silva C, Chen N, Vieira A, Neves J (2012) Enhanced default disk models with SVM+. Expert Syst Appl 39:10140\u201310152","journal-title":"Expert Syst Appl"},{"key":"9434_CR96","doi-asserted-by":"crossref","unstructured":"Ribeiro B, Vieira A, Duarte J, Silva C, Neves J, Liu Q, Sung A (2009) Learning manifolds for bankruptcy analysis. In: M.\u00a0K\u00f6ppen, et\u00a0al. (eds.) International conference on neural information processing, vol 5506. LNCS, Springer, Berlin, pp 722\u2013729","DOI":"10.1007\/978-3-642-02490-0_88"},{"key":"9434_CR97","first-page":"389","volume":"5197","author":"B Ribeiro","year":"2008","unstructured":"Ribeiro B, Vieira A, Neves JC (2008) Supervised Isomap with dissimilarity measures in embedding learning. LNCS 5197:389\u2013396","journal-title":"LNCS"},{"key":"9434_CR98","volume-title":"Pattern classification using ensemble methods","author":"L Rokach","year":"2010","unstructured":"Rokach L (2010) Pattern classification using ensemble methods. World Scientific Publishing, Singapore"},{"issue":"3","key":"9434_CR99","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1016\/j.dss.2012.11.015","volume":"54","author":"C Serrano-Cinca","year":"2013","unstructured":"Serrano-Cinca C, Gutierrez-Nieto B (2013) Partial least square discriminant analysis for bankruptcy prediction. Decis Support Syst 54(3):1245\u20131255","journal-title":"Decis Support Syst"},{"issue":"5","key":"9434_CR100","doi-asserted-by":"crossref","first-page":"1683","DOI":"10.5267\/j.msl.2012.04.021","volume":"2","author":"A Soltan","year":"2012","unstructured":"Soltan A, Mohammadi M (2012) A hybrid model using decision tree and neural network for credit scoring problem. Manage Sci Lett 2(5):1683\u20131688","journal-title":"Manage Sci Lett"},{"issue":"8","key":"9434_CR101","doi-asserted-by":"crossref","first-page":"9305","DOI":"10.1016\/j.eswa.2011.01.042","volume":"38","author":"J Sun","year":"2011","unstructured":"Sun J, Jia M, Li H (2011) AdaBoost ensemble for financial distress prediction: an empirical comparison with data from Chinese listed companies. Expert Syst Appl 38(8):9305\u20139312","journal-title":"Expert Syst Appl"},{"issue":"3","key":"9434_CR102","doi-asserted-by":"crossref","first-page":"818","DOI":"10.1016\/j.eswa.2007.07.045","volume":"35","author":"J Sun","year":"2008","unstructured":"Sun J, Li H (2008) Listed companies\u2019 financial distress prediction based on weighted majority voting combination of multiple classifiers. Expert Syst Appl 35(3):818\u2013827","journal-title":"Expert Syst Appl"},{"issue":"8","key":"9434_CR103","doi-asserted-by":"crossref","first-page":"2254","DOI":"10.1016\/j.asoc.2012.03.028","volume":"12","author":"J Sun","year":"2012","unstructured":"Sun J, Li H (2012) Financial distress prediction using support vector machines: ensemble versus individual. Appl Soft Comput 12(8):2254\u20132265","journal-title":"Appl Soft Comput"},{"key":"9434_CR104","doi-asserted-by":"crossref","unstructured":"Sun Y, Kamel MS, Wang Y (2006) Boosting for learning multiple classes with imbalanced class distribution. In: Proceedings of the sixth IEEE international conference on data mining. pp 592\u2013602","DOI":"10.1109\/ICDM.2006.29"},{"key":"9434_CR105","doi-asserted-by":"crossref","first-page":"3358","DOI":"10.1016\/j.patcog.2007.04.009","volume":"40","author":"Y Sun","year":"2007","unstructured":"Sun Y, Kamela M, Wong A, Wang Y (2007) Cost-sensitive boosting for classification of imbalanced data. Pattern Recogn 40:3358\u20133378","journal-title":"Pattern Recogn"},{"issue":"4","key":"9434_CR106","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1142\/S0218001409007326","volume":"23","author":"Y Sun","year":"2009","unstructured":"Sun Y, Wong AC, Kamel MS (2009) Classification of imbalanced data: a review. Int J Pattern Recognit Artif Intell 23(4):687\u2013719","journal-title":"Int J Pattern Recognit Artif Intell"},{"issue":"2","key":"9434_CR107","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/S0169-2070(00)00034-0","volume":"16","author":"LC Thomas","year":"2000","unstructured":"Thomas LC (2000) A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers. Int J Forecast 16(2):149\u2013172","journal-title":"Int J Forecast"},{"issue":"3","key":"9434_CR108","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1109\/TKDE.2002.1000348","volume":"14","author":"K Ting","year":"2002","unstructured":"Ting K (2002) An instance-weighting method to induce costsensitive trees. IEEE Trans Knowl Data Eng 14(3):659\u2013665","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"9434_CR109","unstructured":"Ting KM (1994) The problem of small disjuncts: its remedy in decision trees. In: Proceedings of the tenth Canadian conference on artificial intelligence. pp 91\u201397"},{"issue":"2","key":"9434_CR110","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.knosys.2008.08.002","volume":"22","author":"CF Tsai","year":"2009","unstructured":"Tsai CF (2009) Feature selection in bankruptcy prediction. Knowl Based Syst 22(2):120\u2013127","journal-title":"Knowl Based Syst"},{"key":"9434_CR111","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1016\/j.knosys.2012.11.005","volume":"39","author":"CF Tsai","year":"2013","unstructured":"Tsai CF, Eberle W, Chu CY (2013) Genetic algorithms in feature and instance selection. Knowl Based Syst 39:240\u2013247","journal-title":"Knowl Based Syst"},{"key":"9434_CR112","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1007\/978-3-540-76280-5_14","volume-title":"Machine learning in document analysis and recognition, studies in computational intelligence","author":"S Tulyakov","year":"2008","unstructured":"Tulyakov S, Jaeger S, Govindaraju V, Doermann D (2008) Review of classifier combination methods. In: Marinai S, Fujisawa H (eds) Machine learning in document analysis and recognition, studies in computational intelligence, vol 90. Springer, Berlin, pp 361\u2013386"},{"key":"9434_CR113","unstructured":"Turney P (2000) Types of cost in inductive concept leaning. In: Workshop on cost-sensitive learning at 7th international conference on machine learning"},{"issue":"1","key":"9434_CR114","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/S0957-4174(99)00016-0","volume":"17","author":"A Vellido","year":"1999","unstructured":"Vellido A, Lisboa P, Vaughan J (1999) Neural networks in business: a survey of applications (1992\u20131998). Expert Syst Appl 17(1):51\u201370","journal-title":"Expert Syst Appl"},{"issue":"9","key":"9434_CR115","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1007\/s00500-009-0490-5","volume":"14","author":"A Verikas","year":"2010","unstructured":"Verikas A, Kalsyte Z, Bacauskiene M, Gelzinis A (2010) Hybrid and ensemble-based soft computing techniques in bankruptcy prediction: a survey. Soft Comput 14(9):995\u20131010","journal-title":"Soft Comput"},{"key":"9434_CR116","doi-asserted-by":"crossref","unstructured":"Vo N, Won Y (2007) Classification of unbalanced medical data with weighted regularized least squares. In: Frontiers in the convergence of bioscience and information technologies. pp 347\u2013352","DOI":"10.1109\/FBIT.2007.20"},{"issue":"5","key":"9434_CR117","doi-asserted-by":"crossref","first-page":"5325","DOI":"10.1016\/j.eswa.2011.11.003","volume":"39","author":"G Wang","year":"2012","unstructured":"Wang G, Ma J (2012) A hybrid ensemble approach for enterprise credit risk assessment based on support vector machine. Expert Syst Appl 39(5):5325\u20135331","journal-title":"Expert Syst Appl"},{"issue":"4","key":"9434_CR118","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/S0167-9236(96)00070-X","volume":"19","author":"BK Wong","year":"1997","unstructured":"Wong BK, Bodnovich TA, Selvi Y (1997) Neural network applications in business: a review and analysis of the literature (1988\u20131995). Decis Support Syst 19(4):301\u2013320","journal-title":"Decis Support Syst"},{"issue":"3","key":"9434_CR119","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/S0378-7206(98)00050-0","volume":"34","author":"BK Wong","year":"1998","unstructured":"Wong BK, Selvi Y (1998) Neural network applications in finance: a review and analysis of literature (1990\u20131996). Inf Manage 34(3):129\u2013139","journal-title":"Inf Manage"},{"key":"9434_CR120","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.inffus.2013.04.006","volume":"16","author":"M Wozniaka","year":"2014","unstructured":"Wozniaka M, Granb M, Corchado E (2014) A survey of multiple classifier systems as hybrid systems. Inf Fusion 16:3\u201317","journal-title":"Inf Fusion"},{"issue":"2","key":"9434_CR121","first-page":"388","volume":"23","author":"G Xie","year":"2013","unstructured":"Xie G, Zhao Y, Jiang M, Zhang N (2013) A novel ensemble learning approach for corporate financial distress forecasting in fashion and textiles supply chains. Math Probl Eng 23(2):388\u2013400","journal-title":"Math Probl Eng"},{"issue":"7","key":"9434_CR122","doi-asserted-by":"crossref","first-page":"8336","DOI":"10.1016\/j.eswa.2011.01.021","volume":"38","author":"Z Yang","year":"2011","unstructured":"Yang Z, You W, Ji G (2011) Using partial least squares and support vector machines for bankruptcy prediction. Expert Syst Appl 38(7):8336\u20138342","journal-title":"Expert Syst Appl"},{"key":"9434_CR123","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.knosys.2012.04.004","volume":"33","author":"CC Yeh","year":"2012","unstructured":"Yeh CC, Lin F, Hsu CY (2012) A hybrid KMV model, random forests and rough set theory approach for credit rating. Knowl Based Syst 33:166\u2013172","journal-title":"Knowl Based Syst"},{"issue":"Pt 2","key":"9434_CR124","first-page":"856","volume":"160","author":"H Yin","year":"2010","unstructured":"Yin H, Leong T (2010) A model driven approach to imbalanced data sampling in medical decision making. Stud Health Technol Inform 160(Pt 2):856\u2013860","journal-title":"Stud Health Technol Inform"},{"key":"9434_CR125","doi-asserted-by":"crossref","unstructured":"Zadrozny B, Elkan C (2001) Learning and making decisions when costs and probabilities are both unknown. In: Proceedings of the seventh international conference on knowledge discovery and data mining. pp 204\u2013213","DOI":"10.1145\/502512.502540"},{"key":"9434_CR126","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1016\/j.procs.2013.05.090","volume":"17","author":"L Zhang","year":"2013","unstructured":"Zhang L, Zhang L, Teng W, Chen Y (2013) Based on information fusion technique with data mining in the application of finance early-warning. Proc Comput Sci 17:695\u2013703","journal-title":"Proc Comput Sci"},{"key":"9434_CR127","doi-asserted-by":"crossref","unstructured":"Zhou L, Lai KK, Yen J (2012) Empirical models based on features ranking techniques for corporate financial distress prediction. Comput Math Appl 64(8):2484\u20132496","DOI":"10.1016\/j.camwa.2012.06.003"},{"key":"9434_CR128","doi-asserted-by":"crossref","DOI":"10.1201\/b12207","volume-title":"Ensemble methods: foundations and algorithms","author":"Z Zhou","year":"2012","unstructured":"Zhou Z (2012) Ensemble methods: foundations and algorithms. CRC Press, Boca Racton"},{"issue":"1","key":"9434_CR129","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1109\/TKDE.2006.17","volume":"18","author":"Z Zhou","year":"2006","unstructured":"Zhou Z, Liu X (2006) Training cost-sensitive neural networks with methods addressing the class imbalance problem. IEEE Trans Knowl Data Eng 18(1):63\u201377","journal-title":"IEEE Trans Knowl Data Eng"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-015-9434-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10462-015-9434-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-015-9434-x","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,24]],"date-time":"2022-05-24T15:23:02Z","timestamp":1653405782000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10462-015-9434-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,10,27]]},"references-count":129,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2016,1]]}},"alternative-id":["9434"],"URL":"https:\/\/doi.org\/10.1007\/s10462-015-9434-x","relation":{},"ISSN":["0269-2821","1573-7462"],"issn-type":[{"value":"0269-2821","type":"print"},{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,10,27]]}}}