Rule learning based on neural network ensemble

A neural network ensemble can significantly improve the generalization ability of neural network-based systems. In this paper, a novel rule-learning algorithm is proposed where the neural network ensemble acts as a front-end processor that generates data for the learning of rules. Experimental results show that the proposed algorithm can generate rules with strong generalization ability.

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