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SVM: Different Kernel functions

  • Instead of computing the dot product on the transformed data, it is math. equivalent to applying a kernel function K(Xi, Xj) to the original data, i.e., K(Xi, Xj) = Φ(Xi) Φ(Xj)
  • Typical Kernel Functions
  • SVM can also be used for classifying multiple (> 2) classes and for regression analysis (with additional parameters)

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