Frequent pattern growth (FP-growth) is a frequent itemset generation technique (similar to Apriori). FP-Growth builds a compact-tree structure and uses the tree for frequent itemset mining and generating rules. It is faster than Apriori and can throw results with large datasets.
Let's go through the steps of FP-Growth:
t_id | Items |
1 | (B, C, D, A) |
2 | (B, C, D) |
3 | (D, A) |
4 | (A, B) |
5 | (A, C, B) |
Items | Frequency |
A | 4 |
B | 4 |
C | 3 |
D | 3 |
Let's set up the minimum threshold or minimum support as 50%:
- Min Support = (5*50/100) = 2.5
- Ceiling of minimum support = 2.5 ~ 3