Introduction to Data Mining Pang-Ning Tan, Michael Steinbach, Vipin Kumar HW 1.

Slide 1Introduction to Data Mining Pang-Ning Tan, Michael Steinbach, Vipin Kumar HW 1 Slide 2Slide 3Slide 4minsup=30% N I F F 5 F 7 F 5 F 9 F 6 F 32 F 4 F 4 F 3 F 6 F 4 F 4 I 2 F 6 NNNNNN => 至少出現 3 次 NN NNNN I 2 I 2 F 4 I 2 F 4 N F: frequent itemset N: non-considered itemset I: infrequent candidate Slide 5Ans: 16/32 Ans: 11/32 Ans: 5/32 Slide 613_ 14_ 15_ 34_ 35_ 45_ =>L5 =>L1 =>L38 8 =>L9 =>L11 =>L3 Slide 7minsup=30%  至少出現 3 次才是 frequent itemset I I C C 5 C 7 C 5 C 9 F 6 MC 32 F 4 F 4 3 C 6 F 4 4 I 2 C 6 II IIII I 2 I 2 4 I 2 4 I closed An itemset is closed if none of its immediate supersets has the same support as the itemset maximal frequent An itemset is maximal frequent if none of its immediate supersets is frequent 10 III