Frequent Pattern Growth Algorithm

I used a total of 13 datasets(from UC Irvine repository) to validate the algorithm and visualized them using pyplot.

Key observation: As the minimum support value increases the time taken by the algo decreases. It implies that, with a lower support the fp-algo must run the mining for the bigger conditional datasets.

Steps included in this algorithm:

1. Construct FP tree
2. Insert FP tree
3. Mine FP tree recursively
4. Conditional pattern base
5. Creating frequent pattern item sets

Implementation:

1. Data preprocessing
2. Creating and updating FP tree
3. Mining and creating conditional FP tree