Fodor, Kitti (2023) Classification of retail loans using decision tree. MULTIDISZCIPLINÁRIS TUDOMÁNYOK: A MISKOLCI EGYETEM KÖZLEMÉNYE, 13 (3). pp. 212-220. ISSN 2062-9737
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Abstract
While there is extensive literature on the prediction of corporate bankruptcies, there is little literature on the classification of retail borrowers. There are several ways to analyse the data, which may yield different results. In this paper, my aim is to predict the default of household loans using decision tree. I found one significant explanatory variable, which was the ratio of the repayment to the contract amount. For my analysis I used two samples with different compositions. Both have high classification accuracy. Overall, the second model is better, with a classification accuracy of 84,4%.
Item Type: | Article |
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Uncontrolled Keywords: | loan default, decision tree, classification, different sample types |
Subjects: | H Social Sciences / társadalomtudományok > HG Finance / pénzügy |
SWORD Depositor: | MTMT SWORD |
Depositing User: | MTMT SWORD |
Date Deposited: | 24 Apr 2024 14:19 |
Last Modified: | 24 Apr 2024 14:19 |
URI: | https://real.mtak.hu/id/eprint/193103 |
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