Apriori is a classical algorithm that is used to mine frequent itemsets to derive various association rules. It will help set up a retail store in a much better way, which will aid revenue generation.
The anti-monotonicity of the support measure is one of the prime concepts around which Apriori revolves. It assumes the following:
- All subsets of a frequent itemset must be frequent
- Similarly, for any infrequent itemset, all its supersets must be infrequent too
Let's look at an example and explain it:
|
Transaction ID |
Milk |
Butter |
Cereal |
Bread |
Book |
|
t1 |
1 |
1 |
1 |
0 |
0 |
|
t2 |
0 |
1 |
1 |
1 |
0 |
|
t3 |
0 |
0 |
0 |
1 |
1 |
|
t4 |
1 |
1 |
0 |
1 |
0 |
|
t5 |
1 |
1 |
1 |
0 |
1 |
|
t6 |
1 |
1 |
1 |
1 |
1 |
We have got the transaction ID and items such as milk, butter, cereal, bread, and book. 1 denotes that item is part of the transaction...
