Computer and Modernization ›› 2021, Vol. 0 ›› Issue (01): 100-104.

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Analysis of Airline Customer Churn by Random Forest Algorithm Based on RFM Model

  

  1. (1. Airport Operations and Transportation Management College, Civil Aviation Flight University of China, Guanghan 618307, China;
    2. Shenzhen Union Business Aviation Co. Ltd., Shenzhen 518000, China)
  • Online:2021-01-28 Published:2021-01-29

Abstract: In recent years, with the rapid development of the aviation market, it is urgent for airlines to control the loss of customers while increasing their market share. Based on the random forest algorithm, according to the data of aviation customers, a loss prediction model is established to predict whether customers have lost. The traditional RFM customer value model is improved and the random forest algorithm is used to predict customer churn. The experimental results show that the customer churn model based on RFM stochastic forest algorithm has a more persuasive index selection, an AUC value reaches 0.92 and the accuracy is higer. The model can be used to predict the loss of airline customers accurately, classify the lost customers and provide marketing strategies for civil aviation enterprises.

Key words: data mining, random forest algorithm, RFM model, customer churn