Association Analysis in Data Mining

hmdahsan113

What is association analysis? Association analysis is a commonly used data mining technique used to discover the relationship between different variables. It analyzes a large amount of data to find those items, attributes or events that frequently appear together, thereby revealing the association between them. For example: Supermarket shopping basket analysis: By analyzing the customer's shopping basket data, it is found that beer and diapers are often purchased together, so as to understand the customer's consumption habits and conduct more effective promotions.

Network behavior analysis: Find which pages are often Email List visited at the same time when users browse the web, so as to understand user interests and optimize the website structure. Application scenarios of association analysis Marketing: Shopping basket analysis: Find the association between products and optimize the placement of products. Customer segmentation: Divide customers into different groups based on purchasing behavior. Recommendation system: Recommend related products based on the user's historical purchase records.





Risk management: Fraud detection: Discover abnormal transaction behavior. Fault prediction: Predict equipment failure by analyzing historical data. Scientific research: Bioinformatics: Discover the association between genes. Social network analysis: Discover community structures in social networks. Basic concepts of association analysis Itemset: A collection of items, such as {beer, diapers, milk}. Support: The support of an item set in a data set refers to the proportion of transactions containing the item set to the total number of transactions.