Chapter 4 - Classifying with probability theory: naïve Bayes

[noisytoken]

When we attempt to classify a document, we multiply a lot of probabilities together to get the probability that a document belongs to a given class. This will look something like p(w0|1)p(w1|1)p(w2|1). If any of these numbers are 0, then when we multiply them together we get 0. To lessen the impact of this, we’ll initialize all of our occurrence counts to 1, and we’ll initialize the denominators to 2

First of all, huge thanks for creating an understandable ML book.

Coming back to question now:

I perfectly, understood the idea behind setting p0Num and p1Num to np.ones, but why you have set p0Denom and p1Denom both to 2?

[JPL-JUNO]

In my opinion, it should be set to the length of the myVocabList multiplied by 1. p0Denom = sum(p0Num) p1Denom = sum(p1Num)