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Aggregative context-aware fitness functions based on feature selection for evolutionary learning of characteristic graph patterns

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We propose aggregative context-aware fitness functions based on feature selection for evolutionary learning of characteristic graph patterns. The proposed fitness functions estimate the fitness of a set of correlated individuals rather than the sum of fitness of the individuals, and specify the fitness of an individual as its contribution degree in the context of the set. | Aggregative context-aware fitness functions based on feature selection for evolutionary learning of characteristic graph patterns