lecture07-AssociationRule

lecture07-AssociationRule - Lecture Note 7 Lecture Note 7...

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Unformatted text preview: Lecture Note 7 Lecture Note 7 Association Rule Mining Association Rule Mining By Gabriel Fung, PhD School of Information Technology and Electrical Engineering The University Of Queensland INFS4203 / INFS7203 Data Mining Introduction Assume we have a store and only sold five items. Transaction records of five customers: Then, we can draw this matrix: P. 2 Customer Items Bought 1 Orange, Soda 2 Milk, Orange, Cleaner 3 Orange, Detergent 4 Orange, Detergent, Soda 5 Cleaner, Soda Orange Cleaner Milk Soda Detergen t Orange 4 Cleaner 1 2 Milk 1 1 1 Soda 2 1 3 Introduction Now, suppose we have thousand of customers Then: Observations Orange and Soda are more likely to be purchased together Detergent is never purchased with cleaner and milk Suggestion If a customer purchase Soda purchase Orange If a customer purchase cleaner not purchase Detergent Action P. 3 Orange Cleaner Milk Soda Detergent Orange 1000 Cleaner 100 1000 Milk 700 50 1000 Soda 900 50 100 1000 Detergen t 50 50 1000 What is Association Rule? P. 4 Given a set of transactions, find rules that will predict the occurrence of an item based on the occurrences of other items in the transaction Note: Implication means co-occurrence, not causality!!! Customer Items Bought 1 Bread, Milk 2 Bread, Diaper, Beer, Eggs 3 Milk, Diaper, Beer, Coke 4 Bread, Milk, Diaper, Beer 5 Bread, Milk, Diaper, Coke {Diaper} {Beer}, {Milk, Bread} {Eggs, Coke}, {Beer, Bread} {Milk}, Example of Association Rules Why Association Rule is Important? Well Many many many many applications Market basket analysis E.g. Amazon Web log mining Product discount P. 5 Terminology Itemset A collection of items E.g. {Milk, Bread, Diaper} k-itemset An itemset that contains k items Support count ( ) Frequency of occurrence of an itemset E.g. ({Milk, Bread,Diaper}) = 2 Frequent Itemset An itemset whose support is greater than or equal to a minsup threshold P. 6 Customer Items Bought 1 Bread, Milk 2 Bread, Diaper, Beer, Eggs 3 Milk, Diaper, Beer, Coke 4 Bread, Milk, Diaper, Beer 5 Bread, Milk, Diaper, Coke Association Rule Formal Definition Definition An implication expression of the form X Y, where X and Y are both itemsets E.g. {Milk, Diaper} {Beer} Evaluation criteria: Support ( s ) Fraction of transactions that contain both X and Y s = P(condition and result) Confidence ( c ) Measures how often items in Y appear in transactions that contain c = P(condition and result) / P(condition) P. 7 Example 1 Given the rule: {Milk, Diaper} {Beer} Support: s = P(condition and result) Confidence: c = P(condition and result) / P(condition) P. 8 Customer Items Bought 1 Bread, Milk 2 Bread, Diaper, Beer, Eggs 3 Milk, Diaper, Beer, Coke 4 Bread, Milk, Diaper, Beer 5...
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lecture07-AssociationRule - Lecture Note 7 Lecture Note 7...

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