AN OVERVIEW OF GENETIC ALGORITHMS FOR ASSOCIATION RULE DISCOVERY

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

Data mining has been a crucial component in the creation of association rules among the numerous item sets in recent years. The process of finding interesting relationships between variables in big databases is called association rule mining. It is considered as one of the key data mining jobs meant to support decision-making. Based on the principles of evolution, genetic algorithms (GAs) have found a solid foundation in the mining of association rules. Optimizing and searching problems can be effectively solved with the use of genetic algorithms, a type of search heuristic. Compared to other formal methods, genetic algorithms have demonstrated the ability to produce findings that are more accurate. Every rule's quality is assessed by the genetic algorithm's fitness function. A genetic algorithm has been developed by numerous academics to extract interesting rules from datasets. For association rule mining, this study includes an overview of genetic algorithms.

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Keywords

Association Rule Mining, Genetic Algorithm, Data Mining, Apriori Algorithm.