Association Rule Mining in R Language

Association Rule Mining

• In idea mining, Association Rule Learning is a popular and well researched method for discovering interesting relations between variables in large database.
• It is intended to identify strong rules discovered in database using different measures of interests.
• The rule found in the sales data of a supermarket would indicated that if a customer buys onions and potatoes together, he or she is likely to also buy hamburger meat.
• Such information can be used as the basis for decisions about marketing activities such as, e.g., promotional pricing or product placements.

Constraints on below measures are used to select useful and best rules of all rules by R. After analyzing these values for all the rules, best rules for WB have been obtained.

E.g. :- Consider rule: {Jack the Ripper (1988)} => {Strawberry Blonde}
Let Jack the Ripper =X and Strawberry Blonde =Y, Then

Support (X U Y) = No of transactions involving both Jack the Ripper and Strawberry Blonde/Total no of transactions.

Confidence= No of transactions where Strawberry Blonde was also bought when Jack the Ripper was bought/ No of transactions where Jack the Ripper was bought

Lift = Ratio of observed support to the expected support