In this section we introduce the multinomial naive Bayes classifier, so called because it is a Bayesian classifier that makes a simplifying (naive) assumption about how the features interact. The intuition of the classifier is shown in Fig. 4 .1. We represent a text document as if it were a bag-of-words, that is, an unordered set of words with their position bag-of-words ignored, keeping only their frequency in the document. In the example in the figure, instead of representing the word order in all the phrases like "I love this movie" and "I would recommend it", we simply note that the word I occurred 5 times in the entire excerpt, the word it 6 times, the words love, recommend, and movie once, and so on.