Association rules
Association rule mining is a technique that focuses upon observing frequently occurring patterns and associations from datasets found in databases such as relational and transactional databases. These rules do not say anything about the preferences of an individual; rather, they rely chiefly on the items within transactions to deduce a certain association. Every transaction is identified by a primary key (distinct ID) called, transaction ID. All these transactions are studied as a group and patterns are mined.
Association rules can be thought of as an if—then relationship. Just to elaborate on that, we have to come up with a rule: if an item A is being bought by the customer, then the chances of item B being picked by the customer too under the same transaction ID (along with item A) is found out. You needs to understand here that it's not a causality, rather, it is co-occurrence pattern that comes to the fore.
There are two elements of these rules:
- Antecedent (if): This is...
