Affinity analysis

In almost all systems and processes, the application of affinity analysis can extract significant knowledge about the unexpected trends [citation needed].

In fact, affinity analysis takes advantages of studying attributes that go together which helps uncover the hidden patterns in a big data through generating association rules.

[1] The support metric in the association rule learning algorithm is defined as the frequency of the antecedent or consequent appearing together in a data set.

This information can then be used for purposes of cross-selling and up-selling, in addition to influencing sales promotions, loyalty programs, store design, and discount plans.

Family Dollar plans to use market basket analysis to help maintain sales growth while moving towards stocking more low-margin consumable goods.

[5] An important clinical application of affinity analysis is that it can be performed on medical patient records in order to generate association rules.

In evidence-based medicine, finding the co-occurrence of symptoms that are associated with developing tumors or cancers can help diagnose the disease at its earliest stage.