Bayesian Learning 1

Read: All the distributed papers AND Chapter 6 of Mitchell, upto but not including the EM algorithm (we cover this later).

Points covered:

1.

Bayes Theorem and MAP Hypotheses

2.

ML Hypotheses

3.

Curious prisoner example

4.

Monte-Hall game example

5.

Monte-Carlo simulation of above

6.

On the accuracy of medical tests

7.

ML and Least Squared Error

8.

Optimal Bayes Classifier/Gibbs Algorithm

9.

Naive Bayes Classifier