Sparse Least Squares Support Vector Machine With Adaptive Kernel Parameters

Sparse Least Squares Support Vector Machine With Adaptive Kernel Parameters

In this paper, we propose an efficient Least Squares Support Vector Machine (LS-SVM) training algorithm, which incorporates sparse representation and dictionary learning. First, we formalize the LS-SVM training as a sparse representation process. Second, kernel parameters are adjusted by optimizing...

Full description

Bibliographic Details
Main Authors: Chaoyu Yang, Jie Yang, Jun Ma
Format: Article
Language:English
Published: Springer 2020-03-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Least squares support vector machine
Sparse representation
Dictionary learning
Kernel parameter optimization
Online Access:https://www.atlantis-press.com/article/125935248/view

Internet

https://www.atlantis-press.com/article/125935248/view

Similar Items