Improved churn prediction in telecommunication industry using data mining techniques

- We have employed Decision Tree, Artificial Neural Networks, K-Nearest Neighbors, and Support Vector Machine to improve churn prediction.
- Using the data of an Iranian mobile company these techniques were experienced and were compared to each other.
- We proposed a hybrid methodology which made considerable improvements to the value of some of evaluations metrics.
- Results showed that above 95% accuracy for Recall and Precision is easily achievable.
- A new methodology for extracting influential features is introduced and experienced.