Showing results for Mining Coverage-Based Fuzzy Rules by Evolutionary Computation.
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The proposed approach consists of three phases: fuzzy-rule generating, fuzzy-rule encoding and fuzzy-rule evolution. In the fuzzy-rule generating phase, a ...
Nov 29, 2001 · The proposed mining approach chooses good individuals in the population for mating, gradually creating better offspring fuzzy rules. A concise ...
This article presents a new differential evolution (DE) algorithm for mining optimized statistically significant fuzzy association rules that are abundant ...
Mining association rules aims to find the relationship among items in the databases and has become one of the most important data mining technologies. Previous ...
In this chapter, we model association rule mining as a Fuzzy multi-objective global optimization problem by considering several measures of strength such as ...
This paper shows how a small number of simple fuzzy if-then rules can be selected for pattern classification problems with many continuous attributes. Our ...
For a set of rules the value of each quality measure is computed as the average of the values for each rule. B. Genetic fuzzy systems for subgroup discovery. A ...
This paper deals with the association rule mining problem under a multi-objective perspective by proposing grammar guided genetic programming (G3P) models, that ...
The experimental results show that the MA outperforms state-of-the-art evolutionary algorithms in terms of solution quality and convergence speed. These ...
This chapter discusses several concepts and issues in the development of Evolutionary Algorithms (EAs) for discovering fuzzy prediction rules.
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