Revision as of 16:49, 3 March 2014

Please leave me comment below if you have any questions, if you notice any errors or if you would like to discuss a topic further.

Questions and Comments

• SCarver Review: Your write-up is excellent. I had to nitpick little concerns in order to produce any feedback worthy comments. I feel like this slecture is a great supplement to my notes from the class so far, and have provided a few additional comments below:

• SCarver Comment 1: Your example to introduce Bayes' Theorem and the statistics behind it was fantastic. Even though you listed the Axioms of Probability as required knowledge, I fully understood what and why you covered the material, and I do not have a large background in this topic.

• SCarver Comment 2: The observation/explanation/inference section was great to explain the link from grinding out probabilities to using Bayes' Theorem. However, the Venn Diagram that was also shown was a bit misleading. While it was correct, I feel it should have been a diagram relating back to the example as well, instead of a generic partition with As and B.

• SCarver Comment 3: From your 3 learning goals at the beginning, I expected 3 sections detailing the parts of the slecture. However, the classification problem and Bayes' Rule sections were combined with very little being mentioned about the nature of a classification problem aside from how to approach and apply Bayes' Theorem to it.

• SCarver Question: In your final section before the conclusion, you appear to use Bayes' Classifier and Bayes' Rule interchangeability. Do they mean the same thing, or can one be used in a different sense as well (It seems like Bayes' Classifier would be a bit more broad of a definition)?

• Additional Questions / Comments

Back to From Bayes' Theorem to Pattern Recognition via Bayes' Rule