基于随机森林回归的国产电影首周票房预测分析  

Predictive analysis of first week box office of domestic movies based on random forest regression

作　　者：宋玉萍 朱家明[1] 杨琴 傅真鑫 徐可 SONG Yuping;ZHU Jiaming;YANG Qin;FU Zhenxin;XU Ke(School of Statistics and Applied Mathematics,Anhui University of Finance and Economics,Bengbu 233030,China;School of Management Science and Engineering,Anhui University of Finance and Economics,Bengbu 233030,China;School of Civil Engineering,Wanjiang Institute of Technology,Ma'anshan 243031,China)

机构地区：[1]安徽财经大学统计与应用数学学院,安徽蚌埠233030 [2]安徽财经大学管理科学与工程学院,安徽蚌埠233030 [3]皖江工学院土木工程学院,安徽马鞍山243031

出　　处：《高师理科学刊》2021年第1期21-26,共6页Journal of Science of Teachers＇College and University

基　　金：国家自然科学基金项目(71934001);教育部人文社会科学研究项目(19YJCZH069);安徽省教研项目(2018jyxm1305)。

摘　　要：针对国产电影首周票房,以2015—2019年国庆院线上映的558部电影为样本,利用网络爬虫技术爬取首周票房、导演及演员阵容、电影评分等17个变量,分别建立最优子集回归和随机森林回归模型,对国产电影首周票房进行预测.通过交叉验证对比2种预测模型的预测精度,探索最优的预测模型.For the first week box office of domestic films,taking 558 films released in National Day cinema from 2015 to 2019 as samples,the web crawler technology was used to crawl 17 variables,such as first week box office,directors,cast,film score,etc.,the optimal subset regression and random forest regression models was established to predict the first week box office of domestic movies.Through cross validation,the prediction accuracy of the two prediction models is compared to explore the best excellent prediction model.

关 键 词：国产电影 首周票房 最优子集回归 随机森林回归 预测 

分 类 号：O29[理学—应用数学] J943[理学—数学]