RT Journal Article ID 32f43ab87bcad084 A1 Terentyev, Alexander N. A1 Bidyuk, Petr I. A1 Mironova, Alexandra V. A1 Medin, Nikolay Yu. T1 Comparison of Data Mining Methods while Credit Rating of Natural Persons JF Journal of Automation and Information Sciences JO JAI(S) YR 2009 FD 2009-11-21 VO 41 IS 10 SP 71 OP 80 K1 intelligent data analysis K1 credit rating K1 scoring model K1 risks estimating K1 analysis and modeling econometric indicators AB The problem of estimating the risks of crediting natural persons by the data mining methods — the cluster analysis, decision trees, artificial neural networks, regression models of discrete choice and Bayesian networks for the purpose of their comparing, is considered. The database of clients of the first branch of the VAB bank is used for constructing the models. The obtained scoring models are estimated by means of the following criteria: common accuracy, errors of the first and second kind. The experimental results, describing the methods and examples of scoring models are given. PB Begell House LK https://www.dl.begellhouse.com/journals/2b6239406278e43e,5b29b44042964b3d,32f43ab87bcad084.html