逻辑回归还是神经网络?零售贷款哪种效果更好?

K. Fodor
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引用次数: 0

摘要

虽然有大量关于公司破产预测的文献,但很少有关于零售借款人分类的文献。匈牙利也是如此。识别谁有成为不良债务人的风险并不容易。有几种分析数据的方法,可能会产生不同的结果。在本文中,我的目的是利用逻辑回归和神经网络来预测家庭贷款的违约。问题是,哪种方法能产生更好的结果?分析表明,神经网络模型产生了最优、最有利的结果。结果表明,该方法的准确度为81.5%。
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Logistic Regression or Neural Network? Which Provides Better Results for Retail Loans?
While there is extensive literature on the prediction of corporate bankruptcies, there is little literature on the classification of retail borrowers. This is also true in Hungary. Recognising who is at risk of becoming a bad debtor is not easy. 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 logistic regression and neural networks. The question is, which method produces the better results?The analyses show that the neural network model produced the best and most favourable results. The accuracy of the best method was found to be 81.5%.
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发文量
7
审稿时长
30 weeks
期刊最新文献
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