Initializing an exemplar based learning process from a RuleNet network

This paper proposes and evaluates a hybrid system based on two machine learning approaches, a neural network and an instance based method. It describes how the knowledge induced by a RuleNet neural network can be used as the initial knowledge for an NGE-like system to start learning. An NGE-based system can be considered an instance based learning method which allows generalization. The proposed collaboration between the two learning methods implemented by the hybrid system is feasible due to the similarity of the concept description languages employed by both. The paper also describes a few experiments conducted; results show that the RuleNet-NGE collaboration is plausible and, in some domains, it improves the performance of NGE on its own.