首页> 外文会议>International Congress on Human-Computer Interaction, Optimization and Robotic Applications >Performance Analysis of and Neural KNN Networks for Predicting Customer Purchases in a Real Retail Department Store
【24h】

Performance Analysis of and Neural KNN Networks for Predicting Customer Purchases in a Real Retail Department Store

机译:绩效分析和神经核武器网络预测客户购物在真正的零售百货商店

获取原文

摘要

Customer Relationship Management technology plays an important role in business performance. Predicting customer behavior enables the business to better address their customers and enhance service level and overall profit. The aim of this paper is to create models that classify clients and predict their purchases in a real retail department store. A real department store retail transactions dataset will be used and two classification/regression models will be tested on it. The first is based on K-Nearest Neighbors and the other one is based on Neural Networks.
机译:客户关系管理技术在业务绩效中起着重要作用。 预测客户行为使业务能够更好地满足客户,并提高服务水平和整体利润。 本文的目的是创建对客户进行分类并预测其在真正的零售部门商店购买的模型。 将使用实际部门商店零售交易DataSet,并将在其上测试两个分类/回归型号。 第一个基于K-Collect邻居,另一个基于神经网络。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号