4fptree - CSE-5120-Fall-2009 Frequent Pattern Tree...

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CSE-5120-Fall-2009 Mining Frequent Patterns without Candidate Generation Jiawei Han, Jian Pei and Yiwen Yin, SIGMOD 2000 Motivations for not using Apriori method : It is costly to handle a large number of can- didate sets. It is tedious to repeatedly scan the database and check the candidate patterns. New approach : Scan the database once to store all essential information in a data structure: FP-tree. The FP-tree is concise and is used in directly generating large itemsets. pattern : a set of items. (itemset) frequent pattern : patterns with support a minimum threshold (large itemset) In one scan, get all the frequent items. e.g. minimum support = 3 TID Items Bought (Ordered) Frequent Items 100 f,a,c,d,g,i,m,p f,c,a,m,p 200 a,b,c,f,l,m,o f,c,a,b,m 300 b,f,h,j,o f,b 400 b,c,k,s,p c,b,p 500 a,f,c,e,l,p,m,n f,c,a,m,p Frequent Pattern Tree (FP-tree) root f:1 c:1 a:1 m:1 p:1 root m:1 b:1 f:2 c:2 a:2 m:1 p:1 f:4 c:3 a:3 m:2 p:2 root c:1 b:1 p:1 b:1 m:1 b:1 Header table head of node-link item f c a b m p f:4 c:3 a:3 m:2 p:2 root c:1 b:1 p:1 b:1 m:1 b:1 23
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Completeness Given a transaction database DB and a sup- port threshold ω , its corresponding FP-tree contains the complete information of DB in relevance to frequent pattern mining. Reasoning : 1. each transaction in the DB is mapped to one path in the FP-tree, 2. the frequent itemset information in each transaction is completely stored in the FP- tree. 3. One path may represent frequent itemsets in multiple transactions without ambiguity because the path representing each trans- action must start from a child node of the root. Complexity in building FP-tree
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This note was uploaded on 04/23/2010 for the course CSC CSC5120 taught by Professor Adafu during the Fall '09 term at CUHK.

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4fptree - CSE-5120-Fall-2009 Frequent Pattern Tree...

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