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B2C E-Commerce Customer Churn Prediction Based on K-Means and SVM

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References

1995Why Satisfied Customers Defect2,226 cited
1996Why Satisfied Customers Defect809 cited
2006Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models574 cited
2018A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees529 cited
2011New insights into churn prediction in the telecommunication sector: A profit driven data mining approach460 cited
2006Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques432 cited
2004Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting425 cited
2016Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction419 cited
2017Retention Futility: Targeting High-Risk Customers Might be Ineffective292 cited
2011Credit card churn forecasting by logistic regression and decision tree225 cited
2009Support vector machines for default prediction of SMEs based on technology credit221 cited
2016A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry214 cited
2018RFM ranking – An effective approach to customer segmentation214 cited
2014

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Churn prediction using comprehensible support vector machine: An analytical CRM application

175 cited

2016Customers churn prediction and marketing retention strategies. An application of support vector machines based on the AUC parameter-selection technique in B2B e-commerce industry161 cited

2020Churn Prediction in Telecommunication using Logistic Regression and Logit Boost160 cited

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2022An Ensemble Model for Predicting Retail Banking Churn in the Youth Segment of Customers26 cited
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2022Development of fading channel patch based convolutional neural network models for customer churn prediction14 cited
2024Predicting customer abandonment in recurrent neural networks using short-term memory13 cited
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