The Apriori implementation

The goal of this chapter is to produce rules of the following form: if a person recommends these movies, they will also recommend this movie. We will also discuss extensions where a person recommends a set of movies is likely to recommend another particular movie.

To do this, we first need to determine if a person recommends a movie. We can do this by creating a new feature Favorable, which is True if the person gave a favorable review to a movie:

all_ratings["Favorable"] = all_ratings["Rating"] > 3

We can see the new feature by viewing the dataset:

all_ratings[10:15]

	UserID	MovieID	Rating	Datetime	Favorable
10	62	257	2	1997-11-12 22:07:14	False
11	286	1014	5	1997-11-17 15:38:45	True
12	200	222	5	1997-10-05 09:05:40	True
13	210	40	3	1998-03-27 21:59:54	False
14	224	29	3	1998-02-21 23:40:57	False

We will sample our dataset to form a training dataset. This also helps reduce the size of the dataset...