Mining Multi-Dimensional Association Single-dimensional rules buys(X,"milk)= buys(X,"bread) Multi-dimensional rules:22 dimensions or predicates Inter-dimension assoc rules(no repeated predicates) age(X, 19-25)A occupation(X, student)= buys(X,"coke hybrid-dimension assoc rules(repeated predicates) age(X, 19-25)A buys(X, popcorn)= buys(X,coke") Categorical Attributes: finite number of possible values,no ordering among values--data cube approach Quantitative Attributes: Numeric, implicit ordering among valuesdiscretization, clustering and gradient approaches9 Mining Multi-Dimensional Association ◼ Single-dimensional rules: buys(X, “milk”)  buys(X, “bread”) ◼ Multi-dimensional rules:  2 dimensions or predicates ◼ Inter-dimension assoc. rules (no repeated predicates) age(X,”19-25”)  occupation(X,“student”)  buys(X, “coke”) ◼ hybrid-dimension assoc. rules (repeated predicates) age(X,”19-25”)  buys(X, “popcorn”)  buys(X, “coke”) ◼ Categorical Attributes: finite number of possible values, no ordering among values—data cube approach ◼ Quantitative Attributes: Numeric, implicit ordering among values—discretization, clustering, and gradient approaches