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Discovering interesting knowledge from a science and technology database with a genetic algorithm
2004
Applied Soft Computing
Data mining consists of extracting interesting knowledge from data. This paper addresses the discovery of knowledge in the form of prediction IF-THEN rules, which are a popular form of knowledge representation in data mining. In this context, we propose a Genetic Algorithm (GA) designed specifically to discover interesting fuzzy prediction rules. The GA searches for prediction rules that are interesting in the sense of being new and surprising for the user. This is done adapting a technique
doi:10.1016/j.asoc.2003.10.002
fatcat:562rvohjyvfl5jkkxwm6q56vja