.png){kind=icon}
返回
On the SVMpath initialization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.sigpro.2011.11.020.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper presents a novel algorithm for the initial configuration to the model selection problem in the two-class support vector machine (SVM) classification when fitting the entire path of SVM solutions for every value of the regularization parameter. Instead of using quadratic programming for initialization in the conventional two-class SVM regularization path fitting methods, we propose a piecewise linear method which reduces the computational cost significantly. Furthermore, an efficient treatment is provided to deal with the singular case where the data set contains linearly dependent points, duplicate points or nearly duplicate points. The performance of the proposed algorithm in terms of computational complexity and the ability to handle singular cases are backed by strict mathematical analysis and proof, and verified by the experimental results. (C) 2011 Elsevier B.V. All rights reserved.
Keyword:
Solution path
Regularization path
Piecewise linear solution
Support vector machine (SVM)
Homotopy method
期刊
IF:
3.6
论文数:
10.0K
被引数:
1.7W
机构
引用论文
分享收藏An SVM-based robust digital image watermarking against desynchronization attacks基于SVM的抗去同步攻击的鲁棒数字图像水印.png)
SIGNAL PROCESSING
SIGNAL PROCESSINGIF3.6
PREAI
分享收藏Porous Lithiophilic Li–Si Alloy‐Type Interfacial Framework via Self‐Discharge Mechanism for Stable Lithium Metal Anode with Superior Rate (Adv. Energy Mater. 37/2021)通过自放电机理的多孔亲锂锂-Si合金型界面框架，用于稳定的锂金属阳极，具有优越的速率 (Adv. Energy Mater. 37/2021)
OAAI
OAAI分享收藏
查看更多内容