首页> 外文会议>IEEE International Conference on Computer Science and Automation Engineering >An incremental algorithm of support vector machine based on distance ratio and k nearest neighbor
【24h】

An incremental algorithm of support vector machine based on distance ratio and k nearest neighbor

机译:基于距离比率和k最近邻的支持向量机的增量算法

获取原文

摘要

For large data sets and data updated situation, incremental training algorithm is an effective solution of support vector machine training. To improve speed of incremental support vector machine training algorithm, this paper combines the distance ratio method and the nearest neighbor method to extract boundary samples, and an incremental support vector machine algorithm based on distance ratio and k nearest neighbor was proposed, this algorithm can eliminate useless samples as far as possible, thus reduces the training time at remaining essentially the same training accuracy.
机译:对于大数据集和数据更新情况,增量训练算法是支持向量机训练的有效解决方案。 为了提高增量支持向量机训练算法的速度,提出了基于距离比和K最近邻居提取边界样本的距离比方法和最近的邻近方法,并且该算法可以消除基于距离比和K最近邻居的增量支持向量机算法。 尽可能无用的样本,从而减少了剩余的培训时间基本相同的训练准确性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号