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Random Forests is a statistical learning theory,using bootsrap re-sampling method form sample sets,and then combining the tree predictors by majority voting so that each tree is grown using a new bootstrap training set.It is widely applied in medicine,bioinformatics,economics and other fields,because of its high prediction accuracy,good tolerance of noisy data,and the law of large numbers they do not overfit.In this paper we first introduce the concept of random forest and the latest research,then provide some important aspects of applications in economics,and a summary is given in the final section.
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Basic Information:
China Classification Code:O212.2
Citation Information:
[1]FANG Kuang-nana,b,WU Jian-bina,ZHU Jian-pinga,b,SHIA Bang-changa,b(a.Department of Statistics,School of Economics,b.Data Mining Center,Xiamen University,Xiamen 361005,China).A Review of Technologies on Random Forests[J].Journal of Statistics and Information,2011,26(03):32-38.
Fund Information:
中央高校基本科研业务费专项资金《基于数据挖掘的数据质量管理研究》(2010221040);; 国家统计局重点项目《金融风险中的统计方法》(2009LZ045)