Data Mining - Association (Rules Function|Model) - Market Basket Analysis

Thomas Bayes

Data Mining - Association (Rules Function|Model) - Market Basket Analysis


Association Rule is an unsupervised data mining function.

It finds rules associated with frequently co-occurring items, used for:

  • market basket analysis,
  • cross-sell,
  • and root cause analysis.

Data Mining Association

An 'association' is not a causality.



Finds items that tend to co-occur in the data and specifies the rules that govern their co-occurrence


Association models are built on a population of interest to obtain information about that population; they cannot be applied to separate data.

An association model returns rules that explain how items or events are associated with each other.

The association rules are returned with statistics that can be used to rank them according to their probability.


  • Find the items that tend to be purchased together and specify their relationship.
  • Useful for product bundling, in-store placement, and defect analysis
  • Improving ordering and location of product
  • Improving supply chain and distribution of product
  • Remind a customer to buy an associated article
  • Remind to mail also an associated person (Gmail Options)



Basket Analysis Joke 1)

Documentation / Reference

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