使用机器学习算法预测打算取消信用卡订阅的客户:案例研究

Fehim Altınışık, H. Yılmaz
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引用次数: 3

摘要

下面的论文介绍了对机器学习算法的分析,该算法用于预测商业银行的客户,这些客户在一年或更短的活动后三个月可能有取消信用卡订阅的风险。对各种数据预处理、抽样和结构化过程的分析使用了由106个变量组成的特征集——描述了客户的交易活动、人口统计、总体满意度和与消费者体验相关的信息。研究还包括深度神经网络与其他通用机器学习算法在两种不同情况下的性能比较。深度神经网络是这项研究的兴趣点,事实证明,它们比一般的机器学习算法表现得更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting Customers Intending To Cancel Credit Card Subscriptions Using Machine Learning Algorithms: A Case Study
Following paper introduces analysis of machine learning algorithms implemented in order to predict customers of commercial bank who may be in risk of cancelling credit card subscriptions by following three months after a year or less activity. An analysis of various data preprocessing, sampling and structuring procedures using a feature set made up of 106 variables -describing customers’ transaction activity, demographics, overall contentment and relative information to consumer experience-also shared. Study also includes performance comparison of Deep Neural Networks against other generic machine learning algorithms on two different cases. Deep Neural Networks were the point of interest of this study and it turns out, them to perform better than generic machine learning algorithms.
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