This book provides a unified framework that describes how
genetic learning can be used to design pattern recognition and
learning systems. It examines how a search technique, the genetic
algorithm, can be used for pattern classification mainly through
approximating decision boundaries. Coverage also demonstrates the
effectiveness of the genetic classifiers vis-a-vis several widely
used classifiers, including neural networks. "
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