A Study on the Prediction of Use of Public Bicycle in Beijing

摘要：

　　In this paper, we introduce two supervised learning algorithms respectively based on random forest and LASSO-logistic regression.By predicting whether different residents with different information such as professions, residential districts and degrees will use public bicycles in the future and compare two algorithms, we seek to provide the government with practical suggestions on the selection of locations and researchers with insights about the selection of algorithms in this interdisciplinary study field.

关键词： Random forest Classification tree LASSO-logistic regression Public bicycle

作者: CHEN Yun CHEN Shengnan CHEN Jiong

作者单位: School of Science,North China University of Technology,Beijing,100041 OwnerIQ,Boston,Massachusetts,02210

会议类型: 国际会议

会议名称: The 7th International Institute of Statistics & Management Engineering Symposium(IISMES2015) (第七届国际统计与管理工程学术研讨会)

会议地点: 山东 日照

会议语种:英文

页码: 525-529

在线出版日期: 2015-08-17（万方平台首次上网日期，不代表论文的发表时间）