Sparse L-norm least squares support vector machine with feature selection

Author:

Shao Yuan-HaiORCID,Li Chun-Na,Liu Ming-Zeng,Wang Zhen,Deng Nai-Yang

Funder

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation

Natural Science Foundation of Inner Mongolia

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference48 articles.

1. Statistical learning theory;Vapnik,1998

2. Support Vector Machines: Theory, Algorithms, and Extensions;Deng,2012

3. Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification;Ding;Pattern Recognit.,2017

4. Improvements on twin support vector machines;Shao;IEEE Trans. Neural Netw.,2011

5. A Dual Coordinate Descent Method for Large-scale Linear SVM;Hsieh,2008

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