文章摘要
王宇,毛玉欣.一种基于卫向量的简化支持向量机模型[J].,2008,(3):446-450
一种基于卫向量的简化支持向量机模型
A model for simplification SVM based on guard vectors
  
DOI:10.7511/dllgxb200803025
中文关键词: 卫向量  支持向量机  训练集  支持向量集
英文关键词: guard vector  support vector machine  training set  support vector set
基金项目:国家自然科学基金资助项目重点项目70431001.
作者单位
王宇,毛玉欣  
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中文摘要:
      针对支持向量机(SVM)在处理大规模训练集时,训练速度和分类速度变慢的缺点,提出了一种基于卫向量的简化SVM模型.用对偶变换及求解线性规划方法提取卫向量,缩小训练集规模;在此基础上对训练得到的支持向量集,用线性相关性去除冗余支持向量,从而达到简化目的.对UCI标准数据集的实验表明 在保证不损失分类精度的前提下,该模型一定程度上改进了传统SVM,缩短了学习时间,取得了良好的效果.
英文摘要:
      A simplification SVM model based on guard vectors is proposed for overcoming the slow speed of training and classification for large scale training set. In order to simplify SVM, the methods of dual transform and linear programming are used to distill guard vectors; based on that, the linearly dependent support vectors are eliminated from SV set. The experiments on the UCI database are done with this algorithm. Results show that in the condition of undeclined correct rate, the running time of this model is reduced and better performance than the standard SVM is achieved.
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