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

  1. 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

Related methods

Referenced by

ScholarGateECLAT (ECLAT (Equivalence Class Clustering and Bottom-up Lattice Traversal)). Retrieved 2026-06-04 from https://scholargate.app/en/machine-learning/eclat