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What is Support Vector Machines and Kernels about?

This document discusses kernels in support vector machines. It explains that kernels allow support vector machines to find nonlinear decision boundaries by transforming data into a higher-dimensional feature space. The kernel trick avoids explicitly carrying out this transformation by defining a kernel function that calculates the inner product in feature space. Common kernel functions include polynomial kernels and Gaussian radial basis function kernels. Kernels must satisfy Mercer

Author

mohammad omar

Language

EN