BANK CREDIT RISK MANAGEMENT THROUGH CLASSIFICATION TREE WITH NEURON NETSAPPLICATION
In the article offered approach to perfection method of estimation of solvency of management borrowers-subjects by the trees of classifications and Neurons networks which have considerable advantages as compared to the coefficient estimation of solvency: the problem of interpretation of results of analysis decides, a methodical tool is comfortable in the use, economical, provides rapid treatment of analytical information, takes into account modern international practice of estimation, there is possibility of simultaneous estimation of quantitative and high-quality indexes.
Year of publication: |
2010
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Authors: | KOLODIZEV O.N. |
Published in: |
ВІСНИК ЕКОНОМІКИ ТРАНСПОРТУ І ПРОМИСЛОВОСТІ. - CyberLeninka. - 2010, 3, p. 105-110
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Publisher: |
CyberLeninka Украинская государственная академия железнодорожного транспорта |
Subject: | КРЕДИТНИЙ РИЗИК | ДЕРЕВО КЛАСИФіКАЦіЙ | НЕЙРОННі МЕРЕЖі | КРЕДИТОСПРОМОЖНіСТЬ ПОЗИЧАЛЬНИКА | CREDIT RISK | CLASSIFICATION TREE | NEURON NETS | CREDITABILITY OF THE BORROWER |
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