Practical explanation of market basket analysis in R with an effective twist

Introduction

Association rule mining is an unsupervised machine learning technique that utilizes the apriori algorithm. Rule mining can be used for uncovering associations between objects in datasets and common trends in the transactions. The most direct application is found in market basket analysis or a “Customers Also Bought” approach. By implementing the apriori algorithm a list of rules are generated as an output to function as if then-scenarios regarding the objects in the set.

A wide spectrum of fields can employ association rules including insurance, medical, telecommunications, manufacturing, etc…