Recent years, data mining techniques have been developed for extracting rules from big data. However, there are some problems to be considered, for example, it is difficult to judge which rules are important and which are not important; and even in simple classification problems with the small number of classes, a various sub-patterns to be considered potentially exist in each class. To solve the above problems, a rule clustering algorithm using multiobjective genetic algorithm is proposed.
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A Rule-Based Classification System Enhanced by Multi-Objective Genetic Algorithm
Semantic Scholar · Computer Science · 2017
Abstract
Recent years, data mining techniques have been developed for extracting rules from big data. However, there are some problems to be considered, for example, it is difficult to judge which rules are important and which are not important; and even in simple classification problems with the small number of classes, a various sub-patterns to be considered potentially exist in each class. To solve the above problems, a rule clustering algorithm using multiobjective genetic algorithm is proposed.