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Analysis and Comparison of Frequent Itemset Mining Techniques
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 106 |
| Year of Publication: 2026 |
| Authors: Surati Sandipkumar B., Desai Apurva A. |
10.5120/ijcad5a86a23dc56
|
Surati Sandipkumar B., Desai Apurva A. . Analysis and Comparison of Frequent Itemset Mining Techniques. International Journal of Computer Applications. 187, 106 ( May 2026), 17-21. DOI=10.5120/ijcad5a86a23dc56
Abstract
Frequent pattern mining is a technique used to mine frequent patterns from transaction dataset. In recent years, continuous efforts have been made in this area. Numerous algorithms have been developed using various data structures and techniques. In this paper, we discuss and compares some popular algorithms, such as Apriori, ECLAT, FP-Growth and PML with an example.
References
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