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Credit card approval model: An application of deep neural networks

机译:信用卡批准模式:深神经网络的应用

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A credit approval system requires deciding approval or rejection the application for supply credit cards based on some personal data of the applicant. In this paper, based on a data sample of 690 applications from the past for credit card requests, we build a predictor model by using a Deep Learning Toolbox 14.0 in Matlab. In the model's description, detailed analysis, and correction of the input data was carried out, the model was implemented taking into account the structure, training, and testing of the deep neural network. Produced binary classifier could be used for many tasks needful to divide data in two classes by some criteria. Neural networks with different numbers of hidden layers are tested to find the best model for the prediction of credit card approval.
机译:信用审批系统需要根据申请人的一些个人数据决定批准或拒绝供应信用卡的申请。 在本文中,基于来自过去用于信用卡请求的690个应用程序的数据样本,我们通过在Matlab中使用深度学习工具箱14.0来构建预测仪模型。 在模型的描述中,详细分析和对输入数据的校正进行了执行,考虑到深度神经网络的结构,训练和测试来实现该模型。 产生的二进制分类器可以用于许多需要通过一些标准划分两类数据的任务。 测试具有不同数量的隐藏层的神经网络,以查找预测信用卡批准的最佳模型。

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