Telecom Customer Churn Prediction Model Combining K-means and XGBoost Algorithm

With the advent of the 5G era, the competition in the telecom industry is increasingly fierce, and the prediction of customer churn has become the key to the survival and development of enterprises. This paper proposes a customer churn prediction model combining K-means and XGBoost algorithm. First, K-means cluster processing is carried out on the training set, then XGBoost is used to train the clustering groups respectively, and finally, the integrated process is carried out. The results show that the model has better generalization ability.