基于机器学习算法的运营商用户流失预测方法  

Prediction Method of Operator Churn based on Machine Learning Algorithm

作　　者：雷中锋 曹旭 宋强 曲延庆 LEI Zhongfeng;CAO Xu;SONG Qiang;QU Yanqing(Shandong Unicom Cloud Network Operation Center,Jinan 250001,China)

机构地区：[1]山东联通公司云网运营中心,山东济南250001

出　　处：《数字通信世界》2023年第1期27-29,共3页Digital Communication World

摘　　要：文章提出了对基于机器学习算法的运营商用户流失预测方法,该方法根据实际的预测需求及标准,对初始数据信息进行预处理,提取用户流失特征,并以此为基础,构建多目标预测层级,设定多层级的用户流失预测结构,提升整体的预测精准度,加快预测速度,完成对用户流失机器学习计算预测模型的构建,并将其用于用户流预测。测试结果表明:机器学习算法运营商用户流失预测测试组最终得出的预测召回率相对较高,表明预测中的误差可控,预测范围扩大,整体的预测针对性更强一些,具有实际的应用创新意义。This paper proposes the design and analysis of the prediction method of operator user churn based on machine learning algorithm.According to the actual prediction needs and standards,the initial data information is preprocessed to extract the characteristics of user churn.Based on this,a multi-objective prediction hierarchy is built,a multi-level user churn prediction structure is set,the overall prediction accuracy is improved,the prediction speed is accelerated,and the machine learning calculation prediction model for user churn is built.The machine learning calculation prediction model for user churn is adopted.The test results show that the predicted recall rate finally obtained by the operator user churn prediction test group of the machine learning algorithm is relatively high,indicating that the error in the prediction is controllable,the prediction range is expanded,and the overall prediction is more targeted,which has practical application innovation significance.

关 键 词：机器学习算法 运营设计 用户流失 预测方法 用户控制 层级运算 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]