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Generate Hash Tree with 31 Candidate Itemset

Description:

Course: Data Mining and Knowledge Discovery (Fall 2021)
Task: Write own program

In the Apriori algorithm, candidate itemsets are partitioned into different buckets and stored in a hash tree. During support counting, itemsets contained in each transaction are also hashed into their appropriate buckets. That way, instead of comparing each itemset in the transaction with every candidate itemset, it is matched only against candidate itemsets that belong to the same bucket

Tan, Pang-Ning, et al. Introduction to Data Mining EBook: Global Edition, Pearson Education, Limited, 2019.

Task:

Screenshot 2023-03-10 150204

Answer:

Screenshot 2023-03-10 150407

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Write a code to generate a hash tree algorithm with candidate item sets

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