方法证据记录
Semi-supervised Apriori Algorithm
The Semi-supervised Apriori algorithm extends the classic Apriori frequent-itemset miner by injecting background knowledge or labeled constraints — such as must-link pairs, forbidden items, or user-specified minimum support thresholds per group — to bias discovery toward practically meaningful association rules and reduce the search space.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Semi-supervised Apriori Algorithm for Constrained Association Rule Mining
分类方法记录 · ml-model / machine-learning
- 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. · URL
- 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
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