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随机森林算法是一种基于决策树的集成学习算法,具有很高的预测准确率,对异常值和噪声具有很好的容忍度,而且不容易出现过拟合,在医学等领域具有广泛的应用。首先介绍了随机森林算法的原理和性质,然后综述了近几年来随机森林算法的改进研究及应用领域,最后对随机森林算法研究做出了总结。
Abstract：Random forest algorithm is an integrated learning algorithm based on decision tree,which has high prediction accuracy,good tolerance to outliers and noise,and is not easy to overfit,and has a wide range of applications in medicine and other fields.This paper first introduces the principle and properties of random forest algorithm,then summarizes the improvement of random forest algorithm and its application fields in recent years,and finally summarizes the research of random forest algorithm.
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基本信息:
DOI：10.16191/j.cnki.hbkx.2019.03.005
中图分类号:TP181
引用信息:
[1]吕红燕,冯倩.随机森林算法研究综述[J].河北省科学院学报,2019,36(03):37-41.DOI:10.16191/j.cnki.hbkx.2019.03.005.
