基于机器学习分类方法的信用卡审批应用
The Application of Credit Approval Based on Machine Learning Classification Method
作者: 莫玉莲 , 费 宇 :云南财经大学统计与数学学院,云南 昆明;
关键词: 信用卡申请; 机器学习分类; 随机森林; Credit Card Application; Machine Learning Classification; Random Forest
摘要:Abstract: The traditional method of credit card approval is often rely on the experience of credit personnel and is to decide whether the credit card applicants meet the conditions of application. Obviously, this approval method has a lot of randomness and instability. In this paper, we take advantages of R software and introduce the six latest machine learning classification method, decision tree clas-sification, AdaBoost, Bagging classification, random forest classifier, support vector machine (SVM) classification, artificial neural network (Ann) into the credit card application management, then establish the automatic application management system, effectively reducing the randomness and instability of the examination and approval results. Finally we calculate the mean square error of all the classification method through 8-fold cross validation and chose the classification with the best effect. The result shows that the classification error of random forest classification is the smallest.
文章引用: 莫玉莲 , 费 宇 (2016) 基于机器学习分类方法的信用卡审批应用。 数据挖掘, 6, 97-105. doi: 10.12677/HJDM.2016.63012
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