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Capacity of Neural Networks and Discriminant Analysis in Classifying Potential Debtors

机译:神经网络在潜在债务人分类中的能力和判别分析

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Identifying potential healthy and unsound customers is an important task. The reduction of loans granted to companies of questionable credibility can influence banks’ performance. A prior identification of factors that affect the condition of companies is a vital element. Among the most commonly used methods we can enumerate discriminant analysis (DA), scoring methods, neural networks (NN), etc. This paper investigates the use of different structure NN and DA in the process of the classification of banks’ potential clients. The results of those different methods are juxtaposed and their performance compared.
机译:确定潜在的健康和不健康的客户是一项重要任务。减少给予信誉欠佳的公司的贷款可能会影响银行的业绩。事先确定影响公司状况的因素是至关重要的因素。在最常用的方法中,我们可以列举判别分析(DA),评分方法,神经网络(NN)等。本文研究了在对银行潜在客户进行分类的过程中,使用不同结构的NN和DA。将这些不同方法的结果并列并比较它们的性能。

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