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In SVMs, what is the role of the kernel function ?
It selects support vectors based on distance metrics.
It reduces the dataset to a single dimension to simplify computations.
Β It is used only for linear SVMs to compute the margin.
It allows computation of inner products in a high-dimensional space without explicitly mapping points.
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