Abstract
This lecture overviews Kernel Methods that have many applications in classification and clustering. It covers the following topics in detail: Kernel Trick. Kernel Matrix. Kernel PCA. Kernel correlation and its use in object tracking. Kernel k-means.
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1D data that can become linearly separable in 2D.
Kernel-Μethods-v2.4-Summary