A Genetic Algorithm as a Learning Method Based on Geometric Representations
A number of different methods combining the use of neural networks and genetic algorithms have been described . This paper discusses an approach for training neural networks based on the geometric representation of the network. In doing so, the genetic algorithm becomes applicable as a common training method for a number of machine learning algorithms that can be similarly represented. The experiments described here were specifically derived to construct claim regions for Fuzzy ARTMAP Neural Networks ,.