Hands-On Unsupervised Learning with Python

Association rules

The last unsupervised approach we're considering is based on the discovery of association rules and it's extremely important in the field of data mining. A common scenario is represented by a collection of commercial transactions made up of a subset of products. The goal is to find out the most important associations between products (for example, the probability of buying P_i and P_j is 70%). Specific algorithms can efficiently mine a whole database, highlighting all the relationships that can be taken into account for strategic and logistic purposes. For example, an online store can employ this method to promote all those items that are frequently bought together with other ones. Moreover, a predictive approach allows simplifying ...