Feature Selection Using Sparse Twin Bounded Support Vector Machine

Xiaohan Zheng; Li Zhang; Leilei Yan

doi:10.1007/978-3-030-63833-7_30

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Feature Selection Using Sparse Twin Bounded Support Vector Machine

Xiaohan Zheng Li Zhang Leilei Yan

Year: 2020 Lecture notes in computer science Pages: 357-369 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-030-63833-7_30

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Keywords:

Support vector machine Computer science Bounded function Feature selection Hinge loss Feature vector Norm (philosophy) Artificial intelligence Pattern recognition (psychology) Dual (grammatical number) Algorithm Machine learning Mathematics

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Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Algorithms and Applications

Physical Sciences → Engineering → Control and Systems Engineering

Blind Source Separation Techniques

Physical Sciences → Computer Science → Signal Processing

Feature Selection Using Sparse Twin Bounded Support Vector Machine

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