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A Survey of Genetic Algorithm for Association Rule Mining
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 67 - Number 20 |
| Year of Publication: 2013 |
| Authors: Gagandeep Kaur, Shruti Aggarwal |
10.5120/11511-7229
|
Gagandeep Kaur, Shruti Aggarwal . A Survey of Genetic Algorithm for Association Rule Mining. International Journal of Computer Applications. 67, 20 ( April 2013), 25-28. DOI=10.5120/11511-7229
Abstract
In recent years, Data Mining is an important aspect for generating association rules among the large number of itemsets. Association Rule Mining is the method for discovering interesting relations between variables in large databases. It is considered as one of the important tasks of data mining intended towards decision making. Genetic algorithm (GA) based on evolution principles has found its strong base in mining Association Rules. Genetic algorithm is a search heuristic which is used to generate useful solutions to optimization and search problems. Genetic algorithm has proved to generate more accurate results when compared to other formal methods available. The fitness function used in Genetic Algorithm evaluates the quality of each rule. Many researchers have proposed genetic algorithm for mining interesting rules from dataset. This paper presents the survey of Genetic Algorithm for Association Rule Mining.
References
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