Machine learning methods for short-term probability of default: A comparison of classification, regression and ranking methods

[2]  Norbert Pavlovic,et al.  A fuzzy Petri net model to estimate train delays , 2013, Simul. Model. Pract. Theory.

[3]  Fernando García,et al.  Credit risk management: A multicriteria approach to assess creditworthiness , 2013, Math. Comput. Model..

[4]  Mykola Pechenizkiy,et al.  An Overview of Concept Drift Applications , 2016 .

[5]  David J. Hand,et al.  Statistical Classification Methods in Consumer Credit Scoring: a Review , 1997 .

[6]  Kurt Hornik,et al.  Multivariate ordinal regression models: an analysis of corporate credit ratings , 2018, Stat. Methods Appl..

[7]  L. Thomas,et al.  The effect of introducing economic variables into credit scorecards: an example from invoice discounting , 2015 .

[8]  D. J. Hand,et al.  Good practice in retail credit scorecard assessment , 2005, J. Oper. Res. Soc..

[9]  Christopher J. C. Burges,et al.  From RankNet to LambdaRank to LambdaMART: An Overview , 2010 .

[10]  H NOH,et al.  Prognostic personal credit risk model considering censored information , 2005, Expert Syst. Appl..

[11]  Christophe Mues,et al.  An empirical comparison of classification algorithms for mortgage default prediction: evidence from a distressed mortgage market , 2016, Eur. J. Oper. Res..

[12]  Eftim Zdravevski,et al.  Weight of evidence as a tool for attribute transformation in the preprocessing stage of supervised learning algorithms , 2011, The 2011 International Joint Conference on Neural Networks.

[13]  Bart Baesens,et al.  Time to default in credit scoring using survival analysis: a benchmark study , 2015, J. Oper. Res. Soc..

[14]  Kenneth Carling,et al.  Corporate credit risk modeling and the macroeconomy , 2007 .

[15]  Tom Fawcett,et al.  An introduction to ROC analysis , 2006, Pattern Recognit. Lett..

[16]  Igor Perko.  Behaviour-based short-term invoice probability of default evaluation , 2017, Eur. J. Oper. Res..

[17]  Thorsten Joachims,et al.  Optimizing search engines using clickthrough data , 2002, KDD.

[18]  Panos M. Pardalos,et al.  A multicriteria approach for rating the credit risk of financial institutions , 2009, Comput. Manag. Sci..

[19]  Jonathan Crook,et al.  The stability of survival model parameter estimates for predicting the probability of default: Empirical evidence over the credit crisis , 2016, Eur. J. Oper. Res..

[20]  Stanislaw Osowski,et al.  Multistage classification by using logistic regression and neural networks for assessment of financial condition of company , 2012, Decis. Support Syst..

[21]  L. Thomas.  A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers , 2000 .

[22]  Davide Anguita,et al.  Delay Prediction System for Large-Scale Railway Networks Based on Big Data Analytics , 2016, INNS Conference on Big Data.

[23]  Masoud Yaghini,et al.  Railway Passenger Train Delay Prediction via Neural Network Model , 2013 .

[24]  D. Sculley,et al.  Combined regression and ranking , 2010, KDD.

[25]  Kyoung-jae Kim,et al.  A corporate credit rating model using multi-class support vector machines with an ordinal pairwise partitioning approach , 2012, Comput. Oper. Res..

[26]  Jake Ansell,et al.  Exploring the performance of small- and medium-sized enterprises through the credit crunch , 2015, J. Oper. Res. Soc..

[27]  Tianqi Chen,et al.  XGBoost: A Scalable Tree Boosting System , 2016, KDD.

[28]  Peiguang Hu.  Predicting and improving invoice-to-cash collection through machine learning/ , 2015 .

[29]  Pavle Kecman,et al.  Online Data-Driven Adaptive Prediction of Train Event Times , 2015, IEEE Transactions on Intelligent Transportation Systems.

[30]  G. Dorfleitner,et al.  Pricing in the online invoice trading market: First empirical evidence , 2017 .

[31]  Paul Schonfeld,et al.  Analyzing passenger train arrival delays with support vector regression , 2015 .

[32]  Senthil Mani,et al.  Prediction of Invoice Payment Status in Account Payable Business Process , 2018, ICSOC.

[33]  Khaled Soufani.  The decision to finance account receivables: the factoring option , 2002 .

[34]  W. Knight.  A Computer Method for Calculating Kendall's Tau with Ungrouped Data , 1966 .

[35]  Johan A. K. Suykens,et al.  Benchmarking state-of-the-art classification algorithms for credit scoring , 2003, J. Oper. Res. Soc..

[36]  Jonathan Crook,et al.  Support vector machines for credit scoring and discovery of significant features , 2009, Expert Syst. Appl..

[37]  J. Suykens,et al.  Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research , 2015, Eur. J. Oper. Res..

[38]  Christian A. Lang,et al.  Using predictive analysis to improve invoice-to-cash collection , 2008, KDD.

[39]  José G. Dias,et al.  Survival mixture models in behavioral scoring , 2015, Expert Syst. Appl..