We want to build a naive Bayes sentiment classifier using add-1 smoothing. Here is our training set:

- the movie has no plot

- honestly pretty boring

+ pretty interesting movie

Test Set:

pretty enjoyable plot

Answer the questions below given the sets above:

1. Compute the prior for the two classes + and -, and the likelihoods for each word given the class (leave in the form of fractions).
2. Would using binary multinomial Naive Bayes change anything?