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Machine Learning · Support vector machines
SVMs find the widest-margin boundary; support vectors, the C parameter, and the kernel trick for non-linear data.
- An SVM picks the boundary with the widest margin; only the points on the margin, the support vectors, define it.
- The kernel trick gives non-linear boundaries without ever computing the high-dimensional features.