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Support Vector Machine Classifier

Support Vector Machine Classifier builds a hyperplane with support vectors to separate marked example points.

Advantages:​

  • It performs well in higher dimension spaces
  • It is robust to outliers
  • It is memory efficient

Disadvantages:​

  • It is computationally expensive
  • It is tricky in selecting the appropriate kernel function