Market Basket Analysis Using High Utility Itemset Mining
_In this post, I will give an alternative to popular techniques in market basket analysis that can help practitioners find high-value patterns rather than just the most frequent ones. We will gain some intuition into different pattern mining problems and look at a real-world example. The full code can be found here. All images are created by the author._
Introduction
I have written a more introductory article about pattern mining already; if you're not familiar with some of the concepts that come up here, feel free to check that one out first.
In short, pattern mining tries to find patterns in data (duuh). Most of the time, this data comes in the form of (multi-)sets or sequences. In my last article, for example, I looked at the sequence of actions that a user performs on a website. In this case, we would care about the ordering of the items.
In other cases, such as the one we will discuss below, we do not care about the ordering of the items. We only list all the items that were in the transaction and how often they appeared.
So for example, transaction 1 contained
