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Predicting Telecom Customer Churn Rate by samailamurtalabaura is a document available to read on EtoBox.

The paper discusses predicting customer churn rates in the telecommunications industry using machine learning models, emphasizing the importance of retaining existing customers due to lower retention costs compared to acquiring new ones. It details the methodology including data analysis, feature engineering, model tuning, and concludes that logistic regression with upsampling outperforms other models. The study highlights the need for larger datasets and diverse prediction algorithms for improved accuracy

Author

samailamurtalabaura

Language

EN