An Embedded Method for Feature Selection Using Kernel Parameter Descent Support Vector Machine

Haiqing Zhu; Ning Bi; Jun Tan; Dongjie Fan

doi:10.1007/978-3-030-03338-5_30

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An Embedded Method for Feature Selection Using Kernel Parameter Descent Support Vector Machine

Haiqing Zhu Ning Bi Jun Tan Dongjie Fan

Year: 2018 Lecture notes in computer science Pages: 351-362 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-030-03338-5_30

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Keywords:

Support vector machine Kernel (algebra) Computer science Radial basis function kernel Kernel method Artificial intelligence Feature selection Pattern recognition (psychology) Polynomial kernel Relevance vector machine Algorithm Mathematics

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Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Machine Learning and ELM

Physical Sciences → Computer Science → Artificial Intelligence

An Embedded Method for Feature Selection Using Kernel Parameter Descent Support Vector Machine

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