Week 7

This week we learned about Apriori algorithm which is used in Association Rule Mining. Association rules are if-then statements that help to show the probability of relationships between data items within large data sets in various types of databases. Association rule mining has a number of applications and is widely used to help discover sales correlations in transactional data or in medical data sets.

Apriori 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.

We also did an exercise to find the frequent item sets and association rule using Apriori algorithm with the given transaction datas.