The Application of Classification Algorithm Combined with K-means in Customer Churning of Telecom

Through the analysis of inland and overseas research results,it is discovered that the cause of the customer prediction for churning in telecom is various and it's difficult to describe the characteristics of churning customers in a general division standard.This article presented a method combining K-means with classification predicting algorithm to analyze the characteristics of churning customers,and the application experiment was carried out based on the customers' data from X subsidiary company of China Unicom in Hunan,using data mining software Clementine 8.1,to establish the prediction model for churning.The result shows that the predicting hit rate of the new method is obviously higher than that of traditional classification predicting algorithm.