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Support Vector Machine

  • Q. What is the basic idea of Support Vector Machine (SVM) and Maximum Margin?
  • Q. How does SVM adjust for classes that cannot be linearly separated?
  • Q. What hyper-parameters are typically tuned in SVM?
  • Q. What are some of the pros/cons of SVM?
  • Q. What is the kernel trick in SVM?
  • Q. What are common choices to use for kernels in SVM?
  • Q. Describe the hinge loss function used in SVM
  • Q. How does hinge loss differ from logistic loss?
  • Q. Explain how SVM can be used in regression problems
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Other Questions in Support Vector Machine
  • What are options to calibrate probabilities produced from the output of a classifier that does not produce natural probabilities?
  • What are the subtypes of Cross Validation?
  • What is Specificity?
  • Explain the concept and working of the Random Forest model
  • How does a learning curve give insight into whether the model is under- or over-fitting?
  • What is the difference between Discriminative and Generative models?
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