Engineering
4 years ago

Unlocking the Power of Nonlinear Data Analysis for Superior Pattern Recognition

Information fusion and data science
Kernel-Based Nonlinear Feature Learning
Haitao Zhao, Zhihui Lai, Henry Leung, Xianyi Zhang

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Kernel-based nonlinear feature learning is crucial in pattern recognition. By using the kernel trick, traditional methods like PCA and LDA can be enhanced to handle nonlinear data better. Through experiments, it has been shown that when the right kernel and parameters are chosen, kernel-based methods can outperform linear methods, especially for nonlinear and inseparable data.