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基于SVM局部后验概率融合方法研究

Study of Fusion Method Based on SVM Local Posteriori Probability
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摘要 研究了基于支持向量机的后验概率的应用,提出了对样本集进行分解,以产生局部后验概率,根据模式的稳健性对局部后验概率进行凸组合融合的方法. In this paper, application of posteriori probability based on SVM is discussed, convex combination method based on pattern robustness is presented that fuse local posteriori probability of decomposing subsets of sample set.
作者 潘继斌
出处 《数学的实践与认识》 CSCD 北大核心 2006年第2期182-185,共4页 Mathematics in Practice and Theory
关键词 支持向量机 后验概率 未确知函数 信息融合 support vector machine posteriori probability unastertained function information fusion .
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参考文献5

  • 1Vapnik V N.Statistical Learning Theory[M].New york,John Wiley & Sons,1998.
  • 2Wahba G.Support Vector Machines,Reproducing Kernel Hilbert Spaces and Randomized GACV[M].In:Advances in kernel Methods Support Vector learning.Massachusetts:MIT press,1999.
  • 3Platt J C.Probabilities for SV Machines[M].In:Advances in Large Margin Classifiers.Massachusetts:MIT press.2000.
  • 4张文生,王珏,戴国忠.支持向量机中引入后验概率的理论和方法研究[J].计算机研究与发展,2002,39(4):392-397. 被引量:8
  • 5潘继斌.未确知函数及其应用[J].湖北师范学院学报(自然科学版),2002,22(3):39-42. 被引量:5

二级参考文献7

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共引文献11

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