Bayesian Learning

CSC 261 - Artificial Intelligence - Weinman



Answer the following questions. Record your answers in your Reading Journal.
  1. Explain equation (20.2) in your own language. Be sure to identify the meaning of each term and its relation to the purpose of the equation.
  2. Equation (20.3) says that when d=d1,d2,
    P(d2 | d1hi)=P(d2 | hi).
    1. Briefly explain what this means in your own words.
    2. Do you feel this assumption is appropriate for the bag of candy example? Briefly explain your position.
  3. Which of Jaynes' desiderata for probability theory do you feel is most likely to be violated using the MAP hypothesis prediction? Briefy explain your selection.
  4. Explain the naive Bayes model in your own words and why it is useful.