Research Of Customer Churn System Based On Decision Tree Algorithm

Data mining is to discovery the interesting information and knowledge, which is useful connotative, and unpredictable, from numerous data. Data mining is a technique that aims to analyze and understand large source data and reveal knowledge hidden in the data. It has been viewed as an important evolution in information processing. Why there have been more attentions to it from researchers or businessmen is due to the wide availability of huge amounts of data and imminent needs for turning such data into valuable information. During the past decade or over, the concepts and techniques on data mining have been presented, and some of them have been discussed in higher levels for the last few years.With the telecom reforming further, the competition in telecom market becomes more and more violent. Customer resource is one of the most important assets for the telecom, and become the focus of competition. Customer retention can have more influence on the company's profit than its scale, market share, margin and other factors. Especially for telecom, almost every telecom is building or is going to build customer churn predictive model. Otherwise, it will lose competitive advantage over its competitor due to lack of prediction for customer churn.The article adopt the decision tree algorithm c5.0,and according to the CRISP-DM (Cross-industry Standard Process for Data Mining) framework. The sequence of demonstration is business understanding, data understanding, data preparation, modeling, evaluation and development and based on the practical data of telecom corporations, the importance of application of DM is analyzed, and the basic description of predictive system is given according to the practical requirement. Finally aiming at the problem of telecom customer churn a lot of historical data is analyzed by using technology of DM.The prediction of customer churn in telecommunication has been a focus problem in our country. The prediction of customer churn uses data mining technology to analyze the history data of lost customers to find out their characteristics and help the telecommunication company adopt proper measure to reduce customer churning in time. It has important meaning for telecommunication companies to reduce their cost and improve their achievement.