Classification and learning using genetic algorithms : applications in bioinformatics and web intelligence
著者
書誌事項
Classification and learning using genetic algorithms : applications in bioinformatics and web intelligence
（Natural computing series）
Springer, c2007
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注記
"with 87 figures and 43 tables"
Includes bibliographical references (p. [277]-307) and index
内容説明・目次
内容説明
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.
目次
Genetic Algorithms.- Supervised Classification Using Genetic Algorithms.- Theoretical Analysis of the GA-classifier.- Variable String Lengths in GA-classifier.- Chromosome Differentiation in VGA-classifier.- Multiobjective VGA-classifier and Quantitative Indices.- Genetic Algorithms in Clustering.- Genetic Learning in Bioinformatics.- Genetic Algorithms and Web Intelligence.
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