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Credit evaluation model of credit card by using the hybrid model of neural network and Logistic regression

机译：神经网络与Logistic回归混合模型的信用卡信用评价模型

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摘要

It is urgent for banks to solve problems in how to identify and judge applicants of credit card, and improve capability of preventing and resisting risk of credit card. To provide effective decisive support to policymaker, to judge the credit card efficiently and intellectually will increase accuracy and efficiency of credit evaluation in process of credit card approval. This text suggests to evaluate credit card by using hybrid model of Neural networks and Logistic regression with their characters of high accuracy of neural networks and high stability of Logistic regression. Real case shows that the accuracy of hybrid model is higher than using neural networks and logistic regression separately. Therefore, This method is feasible and effective.

机译：银行迫切需要解决如何识别和判断信用卡申请人的问题，提高防范和抵御信用卡风险的能力。为决策者提供有效的决定性支持，有效，明智地判断信用卡，将在信用卡审批过程中提高信用评估的准确性和效率。本文建议使用神经网络和Logistic回归的混合模型对信用卡进行评估，其具有神经网络的高精度和Logistic回归的高稳定性的特点。实际案例表明，混合模型的精度高于分别使用神经网络和逻辑回归的精度。因此，该方法是可行和有效的。

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来源
《Wuhan International Conference on E-Business》|2008年|1547-1551|共5页
会议地点 Wuhan(CN)
作者
ZHU Qu Ji; ZHAO Ding Tao;
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作者单位

Haiying Ma@Department of Management Science and Engineering East China University of Science Technology Shanghai 200237 China--;

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关键词
Neural networks; Logistic regression; credit card; credit scoring;

机译：神经网络;逻辑回归信用卡;信用评分;

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4. Credit evaluation model of credit card by using the hybrid model of neural network and Logistic regression [C] . Wuhan International Conference on E-Business . 2008

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Credit evaluation model of credit card by using the hybrid model of neural network and Logistic regression

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