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What influenced Pulp Fiction?

In the video exercise, you were exposed to the value created by Market Basket Analysis in the offline word when applied to retail. In this exercise, you will take the same concepts to build movie recommendations online. When building movie recommendations, it's essential to be able to take in a watched movie by a customer and based on the viewing behavior of the customer and customers like them, to provide actionable recommendations. In this exercise, you will figure out which watched movies are most likely to lead to a recommendation of the movie Pulp Fiction, by figuring out the rules associated with it on the RHS. The transactional dataset movie_trx is loaded in the workspace.

This exercise is part of the course

Market Basket Analysis in R

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Extract rules with Pulp Fiction on the right side
pulpfiction_rules_rhs = apriori(movie_trx, 
                           parameter = list(supp = 0.3,
                                            conf = 0.5), 
                       ___ = list(default = "___",
                                         ___ = "___")) 

# Inspect the first rules
___(___(pulpfiction_rules_rhs))
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