So, the Internet Movie Database (IMDb) has some nicely precompiled datasets that even seem to be updated on a daily basis. Let’s put them to good(?) use. We’ll use two files because the file with ratings only has unique identifiers that have to be merged with the actual names. I’ve downloaded these files before, so they might be a bit out of date. I am not doing this here, but it might be easy to modify the vroom() calls below to always get the up-to-date data gzipped files directly from the website.
tl;dr Using a Naïve Bayesian classifier and a dataset of 1515 video game ratings, I am predicting which developer is most likely to make a game with specific properties (metascore, ESRB rating, genre, platform) in the future.
Naïve Bayesian learning A Naïve Bayes classifier is a very simple method to predict categorial outcomes. A well-known application is text classification, especially predicting whether a text is spam. Here, the classifier tries to use the information about the occurrence of certain words in telling us whether an e-mail message is spam or not.
There is a game I play / try to make myself okay / try so hard to make the pieces all fit / smash it apart / just for the f**k of it (Nine Inch Nails: The Big Come Down)
After this rather distressing opening by the Nine Inch Nails, let’s turn to a more uplifting topic: video games! There is a dataset on Kaggle with ratings for over 4000 video games.
