Churn Prediction in Telecom Using a Hybrid Two-phase Feature Selection Method

Costumer feature selection is one of the core issues of Costumer churn prediction in telecom industry. This paper proposes a hybrid two-phase feature selection method which can effectively reduce feature dimension and promote predicting performance by using both traditional expertise approach and Markov blanket discovery technique. Empirical results of a branch of a Chinese wireless telecom company show that it is a feasible and superior method for telecom costumer feature selection. The results also show better performance of our method than the method based on traditional expertise approach.