In data mining, association rules are useful for analyzing and predicting customer behavior. They play an important part in customer analytics, market basket analysis, product clustering, catalog design and store layout. Programmers use association rules to build programs capable of machine learning.

Why is the association rule especially important in big data analysis?

This technique is particularly appropriate for analyzing the correlations between objects, because it considers conditional interaction among input data sets, and produce the decision rules of the form IF-THEN.

What is association rule learning used for?

Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended to identify strong rules discovered in databases using some measures of interestingness.