Classification and Learning Using Genetic Algorithms
Publication year: 2007
ISBN: 978-3-540-49607-6
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This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. The book is unique in the sense of describing how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries, and it demonstrates the effectiveness of the genetic classifiers vis-à-vis several widely used classifiers, including neural networks. It provides a balanced mixture of theories, algorithms and applications, and in particular results from the bioinformatics and Web intelligence domains.
Subject: Computer Science, Bioinformatics, DOM, Evolutionary computation, Machine learning, Pattern recognition, Variable, Web mining, algorithms, classification, cognition, data mining, electrical engineering, genetic algorithms, intelligence, learning
