RuleMining2A

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Association analysis is often used to discover implicit associations between items in large datasets, and the discovered associations can be expressed in the form of association rules. Association rules are often used to find new cross-selling opportunities. RuleMining2A uses two classic association analysis algorithms, Apriori and FP-Growth, to assist you in finding association rules between items in the dataset.

For example, the rule {pasta} ⇒ {shrimp} found from sales data means that customers who purchase pasta are also likely to purchase shrimp. This information can be used as the basis for marketing decisions such as product recommendations, promotional pricing, and product placement.