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-à-vis several widely used classifiers, including neural
networks.