摘要
随机森林是一种灵活且易于使用的机器学习算法,因为它很简易,既可用于分类也能用于回归任务。在医学、生物信息、环境预测检测等领域有着广泛的应用。为此,本文介绍了随机森林原理及其相关性质,以及它的改进情况及应用,并讨论了以后的改进趋势和方向。
Random forest is a flexible and easy-to-use machine learning algorithm,because it is very simple and can be used for both classification and regression tasks. It has been widely used in the fields of medicine,bioinformatics,environmental prediction and detection. In this paper,the principle of random forest and its related properties,its improvement and application are introduced,and the future improvement trend and direction are discussed.
作者
孙明喆
毕瑶家
孙驰
SUN Mingzhe;BI Yaojia;SUN Chi(Qingdao University of Science and Technology,Information Science and Technology Academy,Qingdao 266016,China)
出处
《现代信息科技》
2019年第20期28-30,共3页
Modern Information Technology
关键词
随机森林
决策树
集成学习
机器学习
random forest
decision tree
integrated learning
machine learning
