20 points
Assigned Tuesday, October 28
Due Friday, November 7
In this mini-homework, you are to develop a new hypothesis based on the 20 labeled training examples you created in the first mini-homework. This hypothesis should be a naïve Bayes classifier with an m-estimate.
In your writeup, give tables representing your conditional probability distributions, with some sort of pseudocount-based prior distribution.
Take your writeup and add it to your description of your target concept, attributes, examples with labels and attribute values, and other classifiers in your personal wiki, which is already linked in from the course wiki. Do not remove your previous results from your wiki; keep everything as a single, comprehensive document.