An effective hybrid learning system for telecommunication churn prediction
A hybrid model learning system for telecom customer churn prediction is proposed. The hybrid model integrates weighted k-means clustering and a rule induction method. The effectiveness of the proposed system is estimated using ROC, AUC and accuracy. The proposed system achieves superior prediction performance against other models. The proposed system can be widely applied in applications of different realms.
telecommunication churn prediction hybrid model clustering rule induction classification