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An Optimized Association Rule mining using Genetic Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 119 - Number 14 |
| Year of Publication: 2015 |
| Authors: Dimple S. Kanani, Shailendra K. Mishra |
10.5120/21134-4063
|
Dimple S. Kanani, Shailendra K. Mishra . An Optimized Association Rule mining using Genetic Algorithm. International Journal of Computer Applications. 119, 14 ( June 2015), 11-15. DOI=10.5120/21134-4063
Abstract
Association Rule Mining technique that attempt to unearthing interesting pattern or relationship between data in large Database. Genetic Algorithm is a search heuristic which is used to generate useful solution for optimization and search problems. Genetic Algorithm based evaluation in Mining Technique is backbone for mining interesting Rule based on GA parameters like fitness function, Crossover Rate, Mutation Rate. The key focus of this synthesize approach is to optimize the rule that generated by mining methodology and to provide more accurate results. The Proposed Approach is to generate rules based on Quantitative dataset, using the concept of threshold - frequent item sets are define as initial population which the first step of Genetic algorithm. Crossover & mutation is applied to generate more combination of rule & can identify Co-occurrence of item sets.
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