Data Association Rules Mining Method Based on Improved Apriori Algorithm
Haotong Wu · 2020
In the existing data mining technology, there are some shortcomings in association rule mining methods. In this paper, aiming at the problem that the mining efficiency of Apriori algorithm is not high when dealing with large database, the genetic algorithm is introduced to improve the Apriori algorithm. This paper first introduces the basic concept and principle of association rules, describes the basic idea of Apriori algorithm in detail, and an improved algorithm based on Partition algorithm is proposed for its shortcomings. Then introducing the principle and operation flow of genetic algorithm in detail, and puts forward the corresponding improvement solutions for the coding scheme and fitness function. Finally, the association rule mining is established by combining genetic algorithm with Apriori algorithm. Compared with other methods, the experimental results show that the proposed method has better performance, higher mining efficiency and better data mining.