URI | http://purl.tuc.gr/dl/dias/1B03D059-B99B-475B-93E1-D6386672833E | - |
Αναγνωριστικό | http://fcds.cs.put.poznan.pl/FCDS2/ArticleDetails.aspx?articleId=110 | - |
Γλώσσα | en | - |
Τίτλος | Application of a genetic algorithm for the credit risk assessment problem | en |
Δημιουργός | Marinakis Ioannis | en |
Δημιουργός | Μαρινακης Ιωαννης | el |
Δημιουργός | Marinaki Magdalini | en |
Δημιουργός | Μαρινακη Μαγδαληνη | el |
Δημιουργός | Zopounidis Konstantinos | en |
Δημιουργός | Ζοπουνιδης Κωνσταντινος | el |
Εκδότης | Politechnika Pozanska | en |
Περίληψη | In this paper, a new procedure that utilizes a Genetic algorithm in order to
solve the Feature Subset Selection problem is presented. The proposed algorithm is
combined with a number of nearest neighbor based classifiers. The proposed Genetic based classification algorithm is applied for the solution of the Credit Risk Assessment
Classification problem. The performance of the algorithm is tested using data from 1411
firms derived from the loan portfolio of a leading Greek Commercial Bank in order to
classify the firms in different groups representing different levels of credit risk. A
comparison of the algorithm with other classification methods, such as SVM, CART is
performed using these data. The algorithm is, also, compared with another metaheuristic algorithm. In this algorithm, the feature subset selection problem is solved using Tabu Search and in the classification phase the Nearest Neighbor Classifier is used. The results obtained using the genetic algorithm for the credit risk assessment classification problem are better than the results of all other classification methods and the metaheuristic algorithm used for the comparisons in this paper. | en |
Τύπος | Peer-Reviewed Journal Publication | en |
Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
Ημερομηνία | 2015-10-01 | - |
Ημερομηνία Δημοσίευσης | 2007 | - |
Βιβλιογραφική Αναφορά | M. Marinaki, Y. Marinakis and C. Zopounidis, (2007), “Application of a Genetic Algorithm for the Credit Risk Assessment Problem”, Foundations of Computing and Decisions Sciences, Vol.32, Issue 2, pp. 139-152. URL:http://fcds.cs.put.poznan.pl/FCDS2/ArticleDetails.aspx?articleId=110
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