Summary – Kernel in Regression

  • A kernel helps in modeling non-linear relationships using a shortcut to high-dimensional feature space.
  • We can think of it as a smart similarity function that unlocks hidden patterns.
  • Kernels are used in algorithms like Support Vector Machines, Kernel Ridge Regression, and Gaussian Processes.

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