Machine learningPattern mining
涌现模式挖掘
涌现模式挖掘（EPM）是一种基于对比的数据挖掘技术，用于识别在从一个数据集（或类别）转移到另一个数据集（或类别）时，其支持度显著增加——或从零开始跃升——的项集。该技术由Dong和Li于1999年提出，主要用于分类、异常检测和趋势分析等任务，这些任务的核心目标是发现两个群体或时间段之间的区分性模式。
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来源
- Dong, G., & Li, J. (1999). Efficient mining of emerging patterns: Discovering trends and differences. ACM SIGKDD, 43–52. DOI: 10.1145/312129.312191 ↗
如何引用本页
ScholarGate. (2026, June 2). Emerging Pattern Mining. ScholarGate. https://scholargate.app/zh/machine-learning/emerging-pattern-mining
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