Improved customer churn prediction model using word order contextualized semantics on customers’ social opinion

Customer churn prediction using improved balanced random forests

Churn prediction is becoming a major focus of banks in China who wish to retain customers by satisfying their needs under resource constraints. In churn prediction, an important yet challenging problem is the imbalance in the data distribution. In this paper, we propose a novel learning method, called improved balanced random forests (IBRF), and demonstrate its application to churn prediction. ...

ADTreesLogit model for customer churn prediction

In this paper, we propose ADTreesLogit, a model that integrates the advantage of ADTrees model and the logistic regression model, to improve the predictive accuracy and interpretability of existing churn prediction models. We show that the overall predictive accuracy of ADTreesLogit model compares favorably with that of TreeNet®, a model which won the Gold Prize in the 2003 mobile customer chur...

A Survey on Customer Churn Prediction using Machine Learning Techniques

The fast expansion of the market in every sector is leading to superior subscriber base for service providers. Added competitors, novel and innovative business models and enhanced services are increasing the cost of customer acquisition. In such a fast set up, service providers have realized the importance of retaining the on-hand customers. It is therefore essential for the service providers t...

Customer Churn Prediction Based on BG / NBD Model

With the rapid development of information technology, most enterprises have built e-commerce platform, which promotes the revolution of operation mode. The focus of competition gradually becomes the customers rather than the products under the increasingly fierce market competition of the E-commerce model. Because of the non-contractual relationship between the customers and the e-commerce plat...

Review on Prediction of Churn Customer Behavior