Introduction to Data Mining Pang-Ning Tan, Michael Steinbach, Vipin Kumar
7
Introduction to Data Min ing Pang-Ning Tan, Michael Steinbach, Vipin K umar HW 1
-
Upload
alexander-roth -
Category
Documents
-
view
37 -
download
0
description
Introduction to Data Mining Pang-Ning Tan, Michael Steinbach, Vipin Kumar. HW 1. N. N. N. N. N. N. N. N. N. N. N. N. N. F: frequent itemset N: non-considered itemset I: infrequent candidate. minsup =30%. => 至少出現 3 次. F. 5. 7. 5. 9. 6. F. F. F. F. F. 3. 2. 4. 4. - PowerPoint PPT Presentation
Transcript of Introduction to Data Mining Pang-Ning Tan, Michael Steinbach, Vipin Kumar
Introduction to Data Mining Pang-Ning Tan, Michael Steinbach, Vipin Kumar
HW 1
minsup=30%
N
I
F
F5
F7
F5
F9
F6
F3 2
F4
F4
F3
F6
F4
F4
I2
F6
N N NN N N
=> 至少出現 3次
NN
N N N N
I2
I2
F4
I2
F4
N
F: frequent itemsetN: non-considered itemsetI: infrequent candidate
Ans: 16/32
Ans: 11/32
Ans: 5/32
13_
14_
15_
34_
35_
45_
=>L5
=>L1
=>L38
8
=>L9
=>L11
=>L3
minsup=30%
至少出現 3次才是 frequent itemset
I
I
C
C5
C7
C5
C9
F6
MC3 2
F4
F4
MC3
C6
F4
MC4
I2
C6
II
I I I I
I2
I2
MC4
I2
MC4
I
An itemset is closed closed if none of its immediate supersets has the same support as the itemsetAn itemset is maximal frequentmaximal frequent if none of its immediate supersets is frequent
10
II I