1Refer to the table below for questions 1-4 and suppose the minimum support is 2.
TID
21. Compute the confidences for the following rules.
G
32. Apply the Apriori procedure by using join operations as described on slide (see slide1) #15.
You need to report all frequent k-itemsets.
The growth tree can the be visualized as follows:
54. Import this table by preparing an appropriate input format for Weka and run Apriori
algorithm. Please use either .arff or csv format by inspecting sample Weka files. Please report
the association rules you find.
Best rules found:
y 2 <conf:(1)> lift:(1.29) lev:(0.05) [0] conv:(0.44)
=n 2 <conf:(1)> lift:(4.5) lev:(0.17) [1] conv:(1.56)
onf:(1)> lift:(1.8) lev:(0.1) [0] conv:(0.89)
conf:(1)> lift:(1.29) lev:(0.05) [0] conv:(0.44)
The list goes on . . .
95. Using Weka, implement Apriori and FP-Growth algorithms on Supermarket data, which is
a sample data set coming with Weka installation. You can find it under Weka folder in your
system. Please report your results with screen shots. You don’t have to report all. Top of the
results is enough for this question. (
10
