Finding association rules with Mahout Frequent Pattern Mining

Association Rule Learning is a method to find relations between variables in a database. For instance, using shopping receipts, we can find association between items: bread is often purchased with peanut butter or chips and beer are often bought together. In this post, we are going to use the Mahout Frequent Pattern Mining implementation to find the associations between items using a list of shopping transactions. For details on the algorithms(apriori and fpgrowth) used to find frequent patterns, you can look at “The comparative study of apriori and FP-growth algorithm” from Deepti Pawar.

EDIT 2014-01-08: updated link to data sample marketbasket.csv (old link was dead). Corrected lift computation. Thanks Felipe F. for pointing the error in the formula.