Aug 25

What are Association rule and APriori Algorithm. How to calculate the related measures.

Apriori[1] is an algorithm for frequent item set mining and association rule learning over relational databases. It proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as those item sets appear sufficiently often in the database. The frequent item sets determined by Apriori can be used to determine association rules which highlight general trends in the database: this has applications in domains such as market basket analysis.

https://www.ibm.com/topics/apriori-algorithm#:~:text=The%20Apriori%20algorithm%20is%20an,items%20called%20itemsets%20in%20data.

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I know not that clear

https://www.solver.com/xlminer/help/association-rules#:~:text=In%20association%20analysis%2C%20the%20antecedent,consequent%20parts%20of%20the%20rule.

https://www.ibm.com/docs/sl/sdm/18.0.0?topic=settings-association-rule-scoring-options

Calculation:

Ref: https://rasbt.github.io/mlxtend/user_guide/frequent_patterns/association_rules/

https://www.kdnuggets.com/2016/04/association-rules-apriori-algorithm-tutorial.html

Support

Confidence:

Lift