Demonstrate proficiency in the following areas:

LO 7.2.2 Math behind Naïve Bayes classifiers

For example:

A. Explain why the denominator can be dropped from Bayes Rule in the context of

classifying a document.

B. Explain the bag of words and the assumptions of the naïve Bayes classifier.

C. Explain why Naïve Bayes calculations are done in log space so that the predicted

class is a linear function of input features.

Reading 7.2: Jurafsky, D., and J. Martin. (2018). Chapter 4. Naïve Bayes and Sentiment Classification, In Speech and Language Processing.

Article  URL: https://web.stanford.edu/~jurafsky/slp3/4.pdf