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Classification and learning using genetic algorithms: applications in Bioinformatics and Web Intelligence
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...
Autores principales: | , |
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Lenguaje: | eng |
Publicado: |
Springer
2007
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/1010767 |
Sumario: | 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. |
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