Create 10 items usually seen in Amazon, K-mart, or any
other supermarkets (e.g. diapers, clothes, etc.).
(1) Create a database of 20 transactions each containing
some of these items. The information can be
stored in a file, or a DBMS.
(2) Repeat (1) by creating 4 additional, different databases each containing 20 transactions.
Using the Apriori algorithm, generate and print out all the association rules and the input transactions for each of the 5 transactional databases you created (support and confidence should be user-specified parameters, so the output should show different support and confidence values with respect to different databases).
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Hi I'm interested in your project. I have skills in JAVA. I will implement the algorithm you said. I'm looking forward to working with you. Regards.
Hi, I have worked with Apriori algorithm for frequent itemset & association rule mining in Python. I can write the code for your project. Let me know if you want to discuss further. Regards, Monir
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