Abstract: In the data of mobile phone users, imbalance problem existed between the replacement users and non replacement users, however traditional date mining pursued the best overall accuracy which led the prediction accuracy of the replacement users overly low. In order to solve this problem, a method of predicting the users who replace phone was proposed based on hierarchical cost sensitive decision tree. The algorithm realized attributes reduction and calculated the importance of attributes by rough set, then a hierarchical structure was built by parting the attributes; finally a cost sensitive decision tree was regarded as the base classifier for the hierarchical structure, the decision tree was constructed with its splitting criterion which included gini index and misclassification cost. Three experiments were made for the users data which from a telecom operator, the results showed that the hierarchical cost sensitive decision tree achieved a better effect on the imbalance user data and balance user data which obtained by under sampling.

Key words: hierarchical structure, decision tree, cost sensitive, imbalance data, prediction of replacing phone