Data mining in Apriori and FP-tree
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This document contains information about frequent itemset mining of a database with transactions containing items. It includes the transaction database with TIDs and items, single item frequencies, candidate itemsets of sizes 1 to 3 generated through frequent itemset mining, and their support counts. It also includes the final frequent itemsets that meet the minimum support threshold.
Data mining in Apriori and FP-tree
- 11. T_ID Item set 100 1, 3, 4 200 2, 3, 5 300 1,2,3, 5 400 2, 5 Scan D Item Set Sup {1} 2 {2} 3 {3} 3 {4} 1 {5} 3 Item set Sup {1} 2 {2} 3 {3} 3 {5} 3 C1 L1 Item Set {1, 2} {1, 3} {1, 5} {2, 3} {2, 5} {3, 5} Item Set Sup {1, 2} 1 {1, 3} 2 {1, 5} 1 {2, 3} 2 {2, 5} 3 {2, 5} 2 Item Set Sup {1, 3} 2 {2, 3} 2 {2, 5} 3 {3, 5} 2 Item Set {2, 3, 5} Item Set Sup {2, 3, 5} 2 L3 L2 C2 C2 C3 Database D
- 13. T_ID Items 100 1, 3, 4 200 2, 3, 5 300 1, 2, 3, 5 400 2, 5 Min support: 2 Item Sup {1} 2 {2} 3 {3} 3 {4} 1 {5} 3 T_ID Item Oder List 100 1, 3, 4 3, 1, 4 200 2, 3, 5 3, 2, 5 300 1, 2, 3, 5 3, 2, 5, 1 400 2, 5 2, 5
- 14. Item Sup Link {2} 3 {3} 3 {5} 3 {1} 2 Root {3}: 1+1+1 {1}: 1 {4}: 1 {2}: 1+1 {5}: 1+1 {1}: 1 {2}: 1 {5}: 1 T_ID Item Oder List 100 1, 3, 4 3, 1, 4 200 2, 3, 5 3, 2, 5 300 1, 2, 3, 5 3, 2, 5, 1 400 2, 5 2, 5