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随机森林与支持向量机分类性能比较
引用本文:黄衍,查伟雄.随机森林与支持向量机分类性能比较[J].软件,2012(6):107-110.
作者姓名:黄衍  查伟雄
作者单位:华东交通大学交通运输与经济研究所
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。

关 键 词:随机森林  支持向量机  分类

Comparison on Classification Performance Between Random Forests and Support Vector Machine
HUANG Yan,ZHA Wei-xiong.Comparison on Classification Performance Between Random Forests and Support Vector Machine[J].Software,2012(6):107-110.
Authors:HUANG Yan  ZHA Wei-xiong
Affiliation:(Institute of Transportation and Economics,East China Jiaotong University,Nanchang 330013,China)
Abstract: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.
Keywords:Random Forests  Support Vector Machine  classification
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