Mining associations with the Apriori rule
Association mining is a technique that can discover interesting relationships hidden in transaction datasets. This approach first finds all frequent itemsets and generates strong association rules from frequent itemsets. Apriori is the most well-known association mining algorithm which identifies frequent individual items first and then performs a breadth-first search strategy to extend individual items to larger itemsets until larger frequent itemsets cannot be found. In this recipe, we will introduce how to perform association analysis using the Apriori rule.
Getting ready
In this recipe, we will use the built-in transaction dataset Groceries to demonstrate how to perform association analysis with the Apriori algorithm in the arules package. Please make sure that the arules package is installed and loaded first.
How to do it...
Perform the following steps to analyze the association rules:
- First, you need to load the
Groceriesdataset:
> data(Groceries...
