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.
Classification and Learning Using Genetic Algorithms
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$227.00
Description
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.
The fact that I have the opportunity to present a second edition of this monograph is an indicator for the growing size of the community concerned with agent-based computational economics. The rapid...
The Office of Scientific & Technical Information (OSTI), is a part of the U.S. Department of Energy (DOE) that houses research and development results from projects funded by the...
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