Performance Analysis of Simplification of Hyperplane Support Vector Machine

Hui Cheng; Jinglong Fang; Daquan Wang; Xingqi Wang

doi:10.11959/j.issn.1000-0801.2015161

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Performance Analysis of Simplification of Hyperplane Support Vector Machine

research and development | 更新时间：2024-06-05

- Performance Analysis of Simplification of Hyperplane Support Vector Machine
- Telecommunications Science Vol. 31, Issue 8, Pages: 78-83(2015)
- 作者机构：
  
  1. 杭州电子科技大学复杂系统建模与仿真教育部重点实验室杭州 310018
  2. 杭州电子科技大学信息工程学院杭州 310018
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2015161
  CLC：
- Published Online：2015-08，
  
  Published：20 August 2015
- 稿件说明：
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Hui Cheng, Jinglong Fang, Daquan Wang, et al. Performance Analysis of Simplification of Hyperplane Support Vector Machine[J]. Telecommunications science, 2015, 31(8): 78-83.
DOI：

Hui Cheng, Jinglong Fang, Daquan Wang, et al. Performance Analysis of Simplification of Hyperplane Support Vector Machine[J]. Telecommunications science, 2015, 31(8): 78-83. DOI： 10.11959/j.issn.1000-0801.2015161.

摘要

与传统支持向量机相比，针对复杂分类问题的超平面支持向量机和针对高噪声数据回归问题的回归型超平面支持向量机，具有支持向量少、测试速度快、计算精度高的优点。然而对不同的样本集，超平面支持向量机的简化效果有所不同，仔细分析了这一现象的原因，得出在支持向量中非约束支持向量所占比率越低则超平面支持向量机简化效果越明显的结论。

Abstract

Comparing with traditional support vector machine，hyperplane support vector machine （HPSVM）and hyperplane support vector machine for regression（HPSVMR）not only reduce the number of support vectors and calculation time but also have comparable accuracy.However，they have different simplification effect on different problems.The reasons for this phenomenon were analyzed，the conclusion that the lower the percentage of non-bound support vectors is，the more obvious the effect of simplification was pointed out.

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references

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