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SVM在不平衡样本集中的应用研究 被引量：2

Advances in Unbalanced Data Sets by SVM
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摘要 Vapnik等人提出基于统计学习理论的支持向量机(SVM,Support Vector Machices)算法,将其运用于模式识别中,取得了较好的效果。但传统的SVM算法针对不平衡样本集时,效果很不理想,很多的科研人员对该问题进行广泛而深入的研究,较为系统的回顾这一个研究分支在过去10年的发展动态。 Vapnick and his collaborators supposed the useful algorithm :Support Vectors Machines( SVMs ) based on statistical learning thorey. The algorithm has been applied to the field of pattern recognition and obtained outstanding results. The traditional SVMs doesn’t show distinguished outputs with the unbalanced data sets. Many scholars have done abroad and deep reaches on this problem to improve the performance of SVMs. The advances in such algorithm studies in the last ten years are reviewed in this paper.
作者 姚程宽
机构地区 安庆医药高等专科学校
出处 《计算机与数字工程》 2007年第10期21-23,69,共4页 Computer & Digital Engineering
关键词 支持向量机 不平衡数据集 统计学习理论 SVMs, unbalanced data sets, statistical learning thorey
分类号 TP31 [自动化与计算机技术—计算机软件与理论]
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参考文献17

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同被引文献16

  • 1穆成坡,黄厚宽,田盛丰,林友芳,秦远辉.基于模糊综合评判的入侵检测报警信息处理[J].计算机研究与发展,2005,42(10):1679-1685. 被引量：49
  • 2刘爽,贾传荧,陈鹏.一种自动选择参数的加权支持向量机算法[J].计算机工程与应用,2006,42(2):64-66. 被引量：9
  • 3郭帆,余敏,叶继华.一种基于分类和相似度的报警聚合方法[J].计算机应用,2007,27(10):2446-2449. 被引量：11
  • 4Valdes A,Shinner K.Probabilistic alert correlation[C]//Proceedings of the 4th International Symposium on Recent Advances in Intrusion Detection,Davis,2001:54-68.
  • 5Giacinto G,Roli F,Didaci L.Fusion of multiple classifiers for intrusion detection in computer networks[J].Pattern Recognit Lett,2003,24(12):1795-1803.
  • 6Vapnik V N.The nature of statistical learning theory[M].New York:Springer,1995.
  • 7Tax D M J,Duin R.Support vector data description[J].Machine Learning,2004,54:45-66.
  • 8Sch?lkopf B,Williamson R,Smola A,et al.Single-class support vector machine,Unsupervised Learning,DagstuhlSeminar-Report 235[R].1999:19-20.
  • 9Muller K R,Mike S,Ratsch G,et al.An introduction to kernel-based learning algorithms[J].IEEE Trans on Neural Net,2001,12:181-201.
  • 10Buhmann M D.Radial basis functions[M].Cambridge:Cambridge University Press,2000:1-38.

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计算机与数字工程
2007年 第10期

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