基于Stacking集成学习的流失用户预测方法

doi:10.3969/j.issn.0255-8297.2020.06.011

Abstract

Abstract: The machine learning algorithm is used to predict the customer loss problem in business activities. Inspired by the idea of Bagging ensemble method, we proposed a Stacking ensemble learning based on bootstrap sampling. By multiple bootstrap sampling of the data set and adding attribute disturbance, multiple copies of the base classifier are trained with the data subset, and the decision result of the base classifier is determined by the vote of the corresponding copy of the base classifier. Experimental results show that the method we proposed in this paper has better performance than all base classifiers and the classical Stacking ensemble method of the same structure in terms of accuracy, precision rate and F1-score.

Key words: Stacking ensemble learning, customer churn prediction, bootstrap sampling, machine learning

CLC Number:

TP391.4

ZHENG Hong, YE Cheng, JIN Yonghong, CHENG Yunhui. Customer Churn Prediction Method Based on Stacking Ensemble Learning[J]. Journal of Applied Sciences, 2020, 38(6): 944-954.

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Customer Churn Prediction Method Based on Stacking Ensemble Learning

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