Affinity analysis is the task of determining when objects are used in similar ways. In the previous chapter, we focused on whether the objects themselves are similar - in our case whether the games were similar in nature. The data for affinity analysis is often described in the form of a transaction. Intuitively, this comes from a transaction at a store—determining when objects are purchased together as a way to recommend products to users that they might purchase.

However, affinity analysis can be applied to many processes that do not use transactions in this sense:

Affinity analysis is usually much more exploratory than classification. At the very least, we often simply rank the results and choose the top five recommendations (or some other number), rather than expect the algorithm to give us a specific answer.

Furthermore, we often don't have the complete dataset we expect for many classification...