计算机科学 ›› 2011, Vol. 38 ›› Issue (12): 247-249.

• 人工智能 • 上一篇    下一篇

Lagrange双支撑向量回归机

郑逢德,张鸿宾   

  1. (北京工业大学计算机学院 北京100124)
  • 出版日期:2018-12-01 发布日期:2018-12-01

Lagrange Twin Support Vector Regression

  • Online:2018-12-01 Published:2018-12-01

摘要: 提出一种快速的支撑向量回归算法。首先将支撑向量回归的带有两组约束的二次规划问题转化为两个小的分别带有一组约束的二次规划问题,而每一个小的二次规划问题又采用一种快速迭代算法求解,该迭代算法能从任何初始点快速收敛,避免了二次优化问题求解,因此能显著提高训练速度。在多个标准数据集上的实验表明,该算法比传统支撑向量机快很多,同时具有良好的泛化性能。

关键词: 支撑向量回归,Langrage支撑向量机,双支撑向量回归,迭代算法

Abstract: This paper proposed a fast support vector regression algorithm. This algorithm converts the ctuadratic programming problems(Qpps) with pair groups of linear inequality constraints to two small size Qpps with only one group of linear inequality constraints. Each of the small size Qpps is solved by an iterative algorithm. The iterative algorithm converges from any starting point and does not need any quadratic optimization packages. Thus this algorithm is fast.The experimental results on several benchmark datasets demonstrate the effectiveness of the proposed algorithm.

Key words: Support vector regression, Lagrange support vector machine, Twin support vector regression, Iterative algorithm

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!