Association Rules Mining

About Association Rules Mining

Association rules are a type of computer science algorithm that can be used to determine relationships between entities or items. Association rules are often used to describe the relations between data items, such as customers and suppliers, in a database.

In a database, association rules reveal the connections among data elements that are hidden by the mere size of the database. For example, suppose a company has 10 different sales representatives who sell products to different customers. If each representative has his own set of customers, then it's not obvious how these 10 salespeople are related to each other.

A common way to discover how these 10 salespeople relate to each other is through an association rule: if one of the salespeople sells products for a specific customer, then there will be an association rule that associates that particular customer with that salesperson.

Association rules can also be used for more complex problems than just finding relationships between two entities in a database—they can be used for pattern discovery in any dataset containing multiple entities (whether they're named as "customers," "users,"

In data mining, the association rule is a technique used to identify patterns in data. It works by looking at how often certain items appear together in a data set, and finds patterns between those items.

And in this app we will learn more about it in detail.