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Overview of the Association Analysis Platform
The Association Analysis platform identifies connections among groups of items in an independent event or transaction. In association analysis, an item is the basic object of interest. For example, an item could be a product, a web page, or a service. An item set is a list of one or more items.
The relationship between two item sets is defined by an association rule. An association rule consists of a condition item set and a consequent item set. Antecedents are the individual items in the condition item set. Association analysis identifies association rules, which predict that a consequent item set will be in a transaction, given that the condition item set is already in the transaction. Some association rules are stronger, and therefore more useful, than others. The following three performance measures describe the strength of an association rule:
Support is the proportion of transactions in which an item set appears. A high value for support indicates that the item set occurs frequently.
Confidence is the proportion of transactions that contain the consequent item set, given that the condition item set is in the transaction. Confidence measures the strength of implication, or the predictive power, of an association rule.
Lift is the ratio of an association rule’s confidence to its expected confidence, assuming that the condition and consequent item sets appear in transactions independently. Lift measures how much the consequent item set depends on the presence of the condition item set. The minimum value for lift is 0.
For more information about association analysis, see Hastie et al. (2009) and Shmueli et al. (2010). For more information about singular value decomposition, see Jolliffe (2002).

Help created on 3/19/2020