# What Is Association Rule in Data Mining?

If you’ve ever seen “Customers who bought this also bought that” while shopping online, you’ve already seen [**association rule mining**](https://learninglabb.com/what-is-association-rule-in-data-mining/) in action.

It’s a technique in **data mining** that finds patterns between items in large datasets. Let’s break it down simply.

### How Association Rules Work

Association rules are like **“if-then” statements**.

Example:  
**If a customer buys bread, they often buy butter too.**

These rules help companies understand how people buy products together. They are widely used in **retail, e-commerce, banking, healthcare, and telecom**.

### Three Key Metrics

When creating these rules, three simple measures are used:

* **Support:** How often an item appears in the data
    
* **Confidence:** How often item B is bought when item A is bought
    
* **Lift:** How strongly item A and item B are related
    

### Different Types of Association Rules

* **Single-dimensional:** Items from the same category (Milk → Bread)
    
* **Multidimensional:** Items from different attributes (Age 20–30 → Buys Protein Powder)
    
* **Boolean:** Yes/No based rules
    
* **Quantitative:** Based on numbers (Income > 50K → Buys SUV)
    

### Why It Matters

Association rule mining helps build **recommendation systems, fraud detection models, and marketing strategies**.

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