What is the kernel trick in Support Vector Machines (SVM)?

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What is the kernel trick in Support Vector Machines (SVM)?

Key points

  • The kernel trick allows SVM to handle complex data by transforming it into a higher-dimensional space.
  • It simplifies the process of finding a linear boundary in the transformed space.
  • This technique is essential for SVM to classify data that is not linearly separable.

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