Machine learningMachine learning
Online FP-growth
Online FP-growth is an incremental extension of the FP-growth algorithm that mines frequent itemsets from continuously arriving transaction streams without rebuilding the full FP-tree from scratch. It updates an existing compact tree structure as new transactions arrive, making it suitable for real-time and high-velocity data environments where a full database scan is impractical.
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Sources
- Cheung, W. & Zaiane, O. R. (2004). Incremental Mining of Frequent Patterns Without Candidate Generation or Support Thr esholding. In Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), pp. 111–118. IEEE. link ↗
- Lee, G., Yun, U. & Ryu, K. H. (2014). Sliding window based weighted maximal frequent pattern mining over data streams. Expert Systems with Applications, 41(2), 694–708. DOI: 10.1016/j.eswa.2013.07.094 ↗