An experimental study on four models of customer churn prediction

Decision tree, neural network and logistic regression were applied frequently as models of customer churn prediction, but the application of them has been mature and they are difficult to be improved. In this paper, Bayesian networks, support vector machines, rough sets and survival analysis were selected for experimental comparison study. An integrated contrast among the four models from the applicability of model in theory and experimental comparison has been processed. Overall, of the four models the Bayesian network model performed best while the survival analysis did worst.