Association Rule Mining
Association Rule Mining is a technique used in Data Science to discover interesting relationships or associations between variables in large datasets. It involves identifying frequent patterns or sets of items in the data and then using these patterns to generate rules that can be used to predict the occurrence of other items or events. The most common application of Association Rule Mining is in market basket analysis, where it is used to identify which products are frequently purchased together. This information can then be used to optimize product placement and promotions in retail stores. Association Rule Mining is also used in other fields such as healthcare, fraud detection, and web usage analysis.
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