Discovering Interesting Association Rules: A Multi-Objective Genetic Algorithm Approach

Provided by: International Journal of Applied Information Systems (IJAIS)
Topic: Data Management
Format: PDF
Association rule mining is considered as one of the important tasks of data mining intended towards decision making process. It has been mainly developed to identify interesting associations and/or correlation relationships between frequent item-sets in datasets. A multi-objective genetic algorithm approach is proposed in this paper for the discovery of interesting association rules with multiple criteria i.e. support, confidence and simplicity (comprehensibility). With Genetic Algorithm (GA), a global search can be achieved and system automation is developed, because the proposed algorithm could identify interesting association rules from a dataset without having the user-specified thresholds of minimum support and minimum confidence.

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