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Apriori 與 FP-Tree 探 勘頻繁項目集

Apriori 與 FP-Tree 探 勘頻繁項目集. Frequent Pattern. 交易資料庫中頻繁的被一起購買的產品 可以做為推薦產品、銷售決策的依據 兩大演算法 Apriori FP-Tree. Apriori. scan. count. Large 1 itemsets 1 2 3 5. Apriori. L 1 1 2 3 5. generate C 2. scan. count. L 2 13 23 25 35. Apriori. L 2 13 23 25 35.

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Apriori 與 FP-Tree 探 勘頻繁項目集

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  1. Apriori與FP-Tree探勘頻繁項目集

  2. Frequent Pattern • 交易資料庫中頻繁的被一起購買的產品 • 可以做為推薦產品、銷售決策的依據 • 兩大演算法 • Apriori • FP-Tree

  3. Apriori scan count Large 1 itemsets 1 2 3 5

  4. Apriori L1 1 2 3 5 generate C2 scan count L2 13 23 25 35

  5. Apriori L2 13 23 25 35 generate C3 scan count L3 235

  6. Apriori缺點 • 效率不佳 • IO時間過長 • Candidate過多

  7. FP-Tree

  8. FP-Tree • min_sup= 50% • min_sup_count= 3

  9. FP-Tree

  10. f b a c m c f Root f:1 f:2 c:2 c:1 a:1 a:2 m:1 b:1 p:1 m:1

  11. Root f:4 c:1 c:3 b:1 b:1 a:3 p:1 m:2 b:1 p:2 m:1

  12. Root f:4 c:1 c:3 b:1 b:1 a:3 p:1 m:2 b:1 p:2 m:1

  13. Root f:3 c:3 a:3

  14. Root f:4 c:1 c:3 b:1 b:1 a:3 p:1 m:2 b:1 p:2 m:1

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