Data Mining

Q.7 explain how to check redundant multilevel association rules.

Checking of Redundant Multilevel Association Rules – A serious side effect of mining multilevel association rules is its generation of many redundant rules across multiple levels of abstraction due to the "ancestor” relationships among items. For example, consider the following rules where "laptop computer” is an ancestor of “IBM laptop computer” based on the concept hierarchy and where X is a variable representing customers who purchased items in all All Electronics transactions.
Rule I – buys(X, “laptop computer”) = buys(X, “HP printer”)
[support = 8%, confidence = 70%]
Rule II – buys(X, “IBM laptop computer”) buys(X, “HP printer”)
[support = 2%, confidence = 72%]
A rule R, is an ancestor of a rule R2, if R, can be obtained by replacing the items in R, by their ancestors in a concept hierarchy. For example rule I is an ancestor of rule II, because “laptop computer” is an ancestor of “IBM laptop computer”. Based on this definition, a rule can be considered redundant if its support and confidence are close to their “expected” values, based on an ancestor of the rule. As an illustration, suppose that rule I has a 70% confidence and 8% support, and that about one-quarter of all “laptop computer” sales are for “IBM laptop computers”. We may except rule II to have a confidence of around 70% (since all data samples of “IBM laptop computers” are also samples of “laptop computer”) and a support of around 2% (i.e. 8% x 1/4). If this is indeed the case, then rule II is not interesting because it does not offer any additional information and is less general than rule I.

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