Frequent Pattern Mining and the Apriori Algorithm: A Concise Technical Overview

These are all related, yet distinct, concepts that have been used for a very long time to describe an aspect of data mining that many would argue is the very essence of the term data mining: taking a set of data and applying statistical methods to find interesting and previously-unknown patterns within said set of data. We aren't looking to classify instances or perform instance clustering; we simply want to learn patterns of subsets which emerge within a dataset and across instances, which ones emerge frequently, which items are associated, and which items correlate with others. It's easy to see why the above terms become conflated. So, let's have a look at this essential aspect of data mining. Foregoing the Apriori algorithm for now, I will simply use the term frequent pattern mining to refer to the big tent of concepts outlined above, even if somewhat flawed (and even if I personally prefer the less often used term association mining).