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Apriori算法

Apriori算法由Agrawal和Srikant于1994年提出,是发现事务数据库中频繁项集和关联规则的基础方法。它采用广度优先、逐层搜索策略,并利用支持度的反单调性(anti-monotone property)高效枚举所有共同出现频率高于用户设定最小阈值的项组合,然后从这些模式中提取可解释的“if-then”规则。

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来源

  1. Agrawal, R. & Srikant, R. (1994). Fast algorithms for mining association rules. Proceedings of the 20th International Conference on Very Large Data Bases (VLDB), 487–499. link
  2. Apriori algorithm. Wikipedia. link

如何引用本页

ScholarGate. (2026, June 3). Apriori Algorithm for Association Rule Mining. ScholarGate. https://scholargate.app/zh/machine-learning/apriori-algorithm

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被引用于

ScholarGateApriori Algorithm (Apriori Algorithm for Association Rule Mining). 于 2026-06-15 检索自 https://scholargate.app/zh/machine-learning/apriori-algorithm · 数据集: https://doi.org/10.5281/zenodo.20539026