陕西师范大学学报（自然科学版）2018，Vol.46Issue(1)：10-15,6.DOI:10.15983/j.cnki.jsnu.2018.01.113
基于LARS-SVR的电影总票房预测模型研究
Film total box office returns forecasting model research based on LARS-SVR
摘要
Abstract
All kinds of factors are taken into account in this paper .Then the least angle regression (LARS) algorithm is applied to implement influence factors selection and the support vector re-gression (SVR) is employed to fit the total box office returns with the selected main factors .The empirical research shows that the volume ,the film format ,the releasing time and the genre of a film are the main influence factors of the total box office returns .And LARS-SVR not only a-voids overfitting phenomenon of SVR by variable selection ,but also retains similar fitting accura-cy with LARS and stepwise regression and has far less forecasting error than the latter two mod -els .Finally ,on the basis of empirical results ,some recommendations are proposed as the refer-ence for the producer ,the marketing company and the cinema operator to make decision .关键词
电影总票房预测/影响因素/最小角回归/支持向量回归Key words
film total box office returns forecasting/influence factors/least angle regression/sup-port vector regression分类
数理科学引用本文复制引用
陈邦丽,徐美萍..基于LARS-SVR的电影总票房预测模型研究[J].陕西师范大学学报（自然科学版）,2018,46(1):10-15,6.基金项目
国家自然科学基金(11501017 ) （11501017 ）
北京市教委科研计划一般项目(理工类)(S Q K M 201610011006 ) （理工类）
