Explain FP Tree Growth Algorithm with a suitable example.

The FP-Growth (Frequent Pattern Growth) algorithm is an efficient method for mining frequent itemsets without the need for candidate generation. It is especially useful in the context of association rule mining, where the goal is to discover patterns that frequently appear together in transactional datasets.

Steps in the FP-Growth Algorithm:

1. Construct the FP-Tree:

   • Scan the dataset to find the frequency of each item.
   • Discard items that do not meet the minimum support threshold.
   • Sort items in descending order of their frequency.
   • Build the FP-Tree by inserting transactions into the tree. The transactions are ordered according to the frequency of items.

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