Introduction
This webpage demonstrates how the Apriori algorithm works for discovering frequent itemsets in a transaction database. A simple version of Apriori is provided that can run in your browser, and display the different steps of the Algorithm. This version of Apriori is not efficient (it is designed only for teaching purposes).
How to use?
1) First, give a transaction database in the text area below, where each line is a transaction, and each transaction is a list of items separated by spaces. For example, this is a transaction database:
apple orange milk
orange tomato bread
apple orange tomato bread
orange bread
apple orange tomato bread
containing four transactions, where the items are apple, orange, milk, bread
Note that each transaction should be sorted and that an item should not appear twice in the same transaction.
2)
Choose a minimum support value (an integer representing the number of transactions that an itemset should appear in to be considered frequent).
3) Then, click on the "Run Apriori" button. The list of frequent itemsets will be displayed with their support. The support of an itemset is the number of transactions that contain the itemset.
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Want to learn more about pattern mining? Check the Pattern Mining course and open-source SPMF software
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