# lecture 6 - Brief Notes on Association Rules Prof Tom Fomby...

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Brief Notes on Association Rules Prof. Tom Fomby Department of Economics Southern Methodist University Dallas, Texas 75275 April, 2011 Unsupervised Learning Method. Neither prediction nor classification. Applications. E.g. Amazon.com sidebars; Grocery store shelving. ( | ) C = consequent items, A = antecedent items Transaction File: Binary Format versus Item List Format Confidence of a rule = ( ) ( | ) ( ) ( ) Lift = ( | ) ( ) : ; Lift = 1 when C and A are independent ( | ) = absolute measure ; Lift = relative measure The Apriori Algorithm (Agrawal and Srikant (1994)) In the first phase build up the item sets that meet the minimum support requirement. First, collect together all of the one-item sets that have minimum support. Then form two-item sets built from the previous minimum support one-item sets and then retain the two-item sets that have minimum support. Then form three-item sets built from the retained one-item and two- item sets and then choose those three-item sets that have minimum support.
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• Spring '08
• TomFomby
• Economics, The Association, binary format, Southern Methodist University, Minimum Support, Prof. Tom Fomby

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