The Apriori Algorithm is a classic algorithm used in data mining for mining frequent itemsets and generating association rules. It operates on a transactional database and identifies patterns by determining the frequency of itemsets in transactions. One of its main characteristics is the use of a breadth-first search strategy to find all frequent itemsets that meet a minimum support threshold. Common use cases include market basket analysis, where retailers analyze purchase patterns to understand customer behavior, and recommendation systems that suggest products based on previously purchased items.
A/B testing compares two versions of a product to optimize performance and improve user engagement.
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AI Fundamentals