Construct fp-tree from a transaction database TId Items bought ordered frequent items 100 f, a, c, d, i,m, p c, a, m, P 200{a,b,c,f,m0} f, C, a, b, my 300{b,J,l,0,w} f, b min support=3 400{b,c,k,s,p c,b, P) 500{a,J,c,el,pmn。cam少 Header table 1. Scan db once find frequent 1-itemset Item frequency head,-+f:4-7c: I (Single item pattern) f 2. Sort frequent items in C:3b:1米b:1 frequency descending b order, f-list a:5 3. Scan dB again m: 2 tb: 1 construct FP-tree F-list=f-c-a-b-m-p +: 2 February 4, 2021 Data Mining: Concepts and Techniques 26February 4, 2021 Data Mining: Concepts and Techniques 26 Construct FP-tree from a Transaction Database {} f:4 c:1 b:1 p:1 c:3 b:1 a:3 m:2 b:1 p:2 m:1 Header Table Item frequency head f 4 c 4 a 3 b 3 m 3 p 3 min_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, w} {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} 1. Scan DB once, find frequent 1-itemset (single item pattern) 2. Sort frequent items in frequency descending order, f-list 3. Scan DB again, construct FP-tree F-list=f-c-a-b-m-p