摘要
针对网站中用户留存度、转化率和忠诚度较低的问题,文中以旅游网站为例,基于logistic回归的机器学习技术,提出一个旅游网站的访问用户行为预测模型。该模型对网站用户的行为数据集合进行预处理,按照固定的比例对数据集合进行分类,验证数据集的分类服从相同的统计分布。最后,建立使用logistic回归机器学习算法相应的模型,对网站用户的行为进行预测。预测结果表明,该模型可以比较准确地预估网站用户的行为。
In allusion to the problems of low user retention degree,conversion rate and loyalty in the website,taking a tourist website as an example,an accessing user behavior prediction model is proposed for the tourist website on the basis of the machine learning technology of logistic regression.The behavior data sets of website users are preprocessed by means of the model.The data sets are classified according to the fixed proportion.It is verified that the data set classification follows the same statistical distribution.The model corresponding to the logistic regression machine learning algorithm is established to predict the behavior of website users.The prediction results show that the model can predict website users′behavior accurately.
作者
徐冬
肖莹慧
XU Dong;XIAO Yinghui(Wuhan College,Wuhan 430212,China)
出处
《现代电子技术》
北大核心
2019年第4期94-96,100,共4页
Modern Electronics Technique
基金
湖北省教育厅科学研究计划指导性项目(B2017383)~~
