机器学习与统计学在银行客户流失预测中的应用

Animesh Shukla
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引用次数: 5

摘要

应用机器学习和统计学的核心概念来预测客户将来是否会离开银行的服务。机器学习模型是通过考虑银行10000个客户的数据来训练的。运用统计技术对数据进行深入的研究,推断数据的不同特征或变量之间的关系。web应用程序在后端使用训练好的模型来预测客户离开银行的概率。因此,该网站可以证明是非常有用的银行经理和银行的决策者了解哪些客户可能会离开银行的服务,并可以通过制定一些新的政策来留住他们。
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Application of Machine Learning and Statistics in Banking Customer Churn Prediction
Application of the core concepts of Machine Learning and Statistics for predicting whether the customer would leave the services of the bank in future or not. Machine learning model is trained by considering the data of 10,000 customers of the bank. Statistical Techniques are applied so as to investigate the data in depth and infer the relationships between different features or variables of data. The web application uses the trained model in the backend to predict the probability of the customer leaving the bank. Hence, the website can prove to be extremely useful for the bank managers and decision makers of the bank to get an idea of those customers who are likely to leave the services of the bank in future and can retain them by formulating some new policies.
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