Multiple Kernel-Based Discriminant Analysis via Support Vectors for Dimension Reduction

Multiple Kernel-Based Discriminant Analysis via Support Vectors for Dimension Reduction

Kernel-based discriminant analysis is an effective nonlinear mechanism for pattern analysis. Conventional kernel-based discriminant analysis mainly based on a single kernel function may be insufficient when dealing with datasets with complicated geometric structures. A combination of multiple kernel...

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Bibliographic Details
Main Authors: Shan Zeng, Chongjun Gao, Xiuying Wang, Liang Jiang, Dagan Feng
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Kernel discriminant analysis
multi-kernel SVM
support vectors
Online Access:https://ieeexplore.ieee.org/document/8664467/

Internet

https://ieeexplore.ieee.org/document/8664467/

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