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Supervised Learning

  • Q. How to determine threshold/decision rule for a classification model?
  • Q. Understanding Probability Outputs in Classification Algorithms
  • Q. What do you mean by calibration quality? How can calibration quality be detected from the output of an algorithm?
  • Q. What are options to calibrate probabilities produced from the output of a classifier that does not produce natural probabilities?
  • Q. What happens if a category has a zero frequency within a class, and how is this issue commonly addressed (Naive Bayes)?
  • Q. How are continuous features incorporated into Naive Bayes?
  • Q. What are the Pros/Cons of Naive Bayes? 
  • Q. How does SVM adjust for classes that cannot be linearly separated?
  • Q. What hyper-parameters are typically tuned in SVM?
  • Q. Describe the hinge loss function used in SVM
  • Q. How does discriminant analysis work at a high level?
  • Q. What differentiates Linear Discriminant Analysis (LDA) from Quadratic Discriminant Analysis (QDA)?
  • Q. What is the difference between QDA and Gaussian Mixture Models (GMM)?
  • Q. What are some pros and cons of Discriminant Analysis?
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Other Questions in Supervised Learning
  • Discuss Softmax activation function
  • Explain the difference between Entropy, Gini, and Information Gain
  • What are some desirable properties of estimators?
  • What is Stratified Sampling?
  • What are the main components of a Bayesian Model?
  • What is the difference between parametric and non-parametric models?
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