Association Analysis in a Nutshell

In this post, I will be explaining the uses and how can one apply association analysis onto solving real-life issues. Let’s begin by defining Association analysis.

What is Association analysis?

In short, association analysis is used to determine how input variables are associated with the outputs or the relationships between them. Inputs are termed “antecedents” and outputs are termed “consequents”.

Possible applications and uses for Association analysis often include the Market basket analysis. The Market basket analysis is useful to determine what items are frequently purchased by consumers. By using the results obtained, the store can create new discounts, bundles or even a change in their layout to increase sales of targeted products.

An example of the Market basket transactions are as follows:

Itemset 1: {jam,ham,bread}

Itemset 2: {jam,milk,bread}

Itemset 3: {milk,rice,jam}

By running an Association analysis on the Market basket transactions, the analyst can obtain various relationships between the items a customer buys. For example, jam -> bread (If a customer buys jam, he/she may buy bread).

One of the most commonly used algorithms for Association analysis is the Apriori…