随机森林与支持向量机分类性能比较  

Comparison on Classification Performance Between Random Forests and Support Vector Machine

作　　者：黄衍[1] 查伟雄[1] 

机构地区：[1]华东交通大学交通运输与经济研究所,南昌330013

出　　处：《软件》2012年第6期107-110,共4页Software

摘　　要：随机森林是一种性能优越的分类器。为了使国内学者更深入地了解其性能,通过将其与已在国内得到广泛应用的支持向量机进行数据实验比较,客观地展示其分类性能。实验选取了20个UCI数据集,从泛化能力、噪声鲁棒性和不平衡分类三个主要方面进行,得到的结论可为研究者选择和使用分类器提供有价值的参考。Random Forests is an excellent classifier.In order to make Chinese scholars fully understand its performance,this paper compared it with Support Vector Machine widely used in China by means of data experiments to objectively show its classification performance.The experiments,using 20 UCI data sets,were carried out from three main aspects：generalization,noise robustness and imbalanced data classification.Experimental results can provide references for classifiers＇choice and use.

关 键 词：随机森林 支持向量机 分类 

分 类 号：O235[理学—运筹学与控制论]