NeuroEvolution of Augmenting Topologies with Learning for Data Classification


Appropriate topology and connection weight are two very important properties a neural network must have in order to successfully perform data classification. In this paper, we propose a hybrid training scheme Learning-NEAT (L-NEAT) for data classification problem. L-NEAT simplifies evolution by dividing the complete problem domain into sub tasks and learn… (More)


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