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Discuss Association Rule Mining and Apriori Algorithm. Apply AR Mining to find all frequent item sets and association rules for the following dataset: Minimum Support Count = 2 Minimum Confidence = 70
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written 7.2 years ago by | • modified 6.9 years ago |
Support count = 2
x/9 * 100 = 70
x = 6.3
step 1: Generating 1-itemset frequent pattern
Scan D for count of each candidate
C1
Item Set | count |
---|---|
{1} | 7 |
{2} | 6 |
{3} | 6 |
{4} | 2 |
{5} | 2 |
Compare candidate support count with minimum support count
L1
Item Set |
---|
{1} |
{2} |
{3} |
{4} |
{5} |
Step 2 : Generate C2- itemset Frequent Pattern
Generate C2 candidate from L1
C2
Item Set | count |
---|---|
{1,2} | 3 |
{1,3} | 5 |
{1,4} | 1 |
{1,5} | 2 |
{2,3} | 2 |
{2,4} | 2 |
{2,5} | 2 |
{3,4} | 0 |
{3,5} | 1 |
{4,5} | 0 |
Compare candidate support count with minimum support count
L2
Item Set |
---|
{1,2} |
{1,3} |
{1,5} |
{2,3} |
{2,4} |
{2,5} |
Step 3: Generating 3- itemset Frequent Pattern
C3
Item Set | count |
---|---|
{1,2,3} | 2 |
{1,2,4} | 1 |
{1,2,5} | 2 |
{2,3,4} | 0 |
{2,3,5} | 1 |
{3,4,5} | 0 |
{45,1} | 0 |
Compare candidate support count with minimum support count L3
Item Set | count |
---|---|
{1,2,3} | 2 |
{1,2,5} | 2 |