Machine learningMachine learning
半监督Apriori算法
半监督Apriori算法在经典的Apriori频繁项集挖掘器的基础上，通过注入背景知识或标签约束（例如必须链接对、禁止项或用户指定的每组最小支持阈值）来扩展，从而将发现偏向于实际有意义的关联规则并减小搜索空间。
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来源
- 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 ↗
- Liu, B., Hsu, W., & Ma, Y. (1999). Mining association rules with multiple minimum supports. Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 337–341. DOI: 10.1145/312129.312274 ↗
如何引用本页
ScholarGate. (2026, June 3). Semi-supervised Apriori Algorithm for Constrained Association Rule Mining. ScholarGate. https://scholargate.app/zh/machine-learning/semi-supervised-apriori-algorithm
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