Machine learningPattern mining
ECLAT Frequent-Itemset Mining
ECLAT, introduced by Mohammed Zaki in 2000, mines frequent itemsets using a vertical data representation: instead of scanning transactions, it stores for each item the set of transaction IDs (a tidset) that contain it, and computes the support of any itemset by intersecting tidsets. This depth-first, intersection-based approach is fast and memory-efficient, an alternative to Apriori's horizontal scans and FP-Growth's tree.
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Sources
- Zaki, M. J. (2000). Scalable algorithms for association mining. IEEE Transactions on Knowledge and Data Engineering, 12(3), 372–390. DOI: 10.1109/69.846291 ↗