Multi-dimension association rule mining based on Adaptive Genetic Algorithm

This paper proposes a method of mining multi-dimension association rule based on the Adaptive Genetic Algorithm (AGA) with crossover matrix and mutation matrix. In this association rule mining system, selection, mutation, and crossover are all parameter-free in evolution process. Results show that:...

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Bibliographic Details
Main Authors: Min Wang, Qin Zou, Caihui Liu
Format: Conference Proceeding
Language:English
Subjects:
Adaptive Genetic Algorithm
Association rules
Biological cells
Crossover Matrix
Genetic algorithms
Indexes
Itemsets
Multi-dimension Association Rule
Mutation Matrix
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Summary:This paper proposes a method of mining multi-dimension association rule based on the Adaptive Genetic Algorithm (AGA) with crossover matrix and mutation matrix. In this association rule mining system, selection, mutation, and crossover are all parameter-free in evolution process. Results show that: combined with the adaptive genetic algorithm, the precision and efficiency of mining association rules is improved.
DOI:10.1109/URKE.2011.6007931