Author: Derouiche, Abir; Layeb, Abdesslem; Habbas, Zineb
Title: Mining Interesting Association Rules with a Modified Genetic Algorithm Cord-id: fxn8n4yv Document date: 2021_2_22
ID: fxn8n4yv
Snippet: Association Rules Mining is an important data mining task that has many applications. Association rules mining is considered as an optimization problem; thus several metaheuristics have been developed to solve it since they have been proven to be faster than the exact algorithms. However, most of them generates a lot of redundant rules. In this work, we proposed a modified genetic algorithm for mining interesting non-redundant association rules. Different experiments have been carried out on sev
Document: Association Rules Mining is an important data mining task that has many applications. Association rules mining is considered as an optimization problem; thus several metaheuristics have been developed to solve it since they have been proven to be faster than the exact algorithms. However, most of them generates a lot of redundant rules. In this work, we proposed a modified genetic algorithm for mining interesting non-redundant association rules. Different experiments have been carried out on several well-known benchmarks. Moreover, the algorithm was compared with those of other published works and the results found proved the efficiency of our proposal.
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