Title:
Classification and learning using genetic algorithms : applications in bioinformatics and web intelligence
Personal Author:
Series:
Natural computing series
Publication Information:
Berlin : Springer-Verlag, 2007
ISBN:
9783540496069
General Note:
Available online version
Added Author:
Electronic Access:
FulltextAvailable:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000010195457 | QA402.5 B36 2007 | Open Access Book | Book | Searching... |
Searching... | 30000010150386 | QA402.5 B36 2007 | Open Access Book | Book | Searching... |
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Summary
Summary
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.
Table of Contents
| Introduction |
| Genetic Algorithms |
| Supervised Classification Using Genetic Algorithms |
| Theoretical Analysis of the GA-Classifier |
| Variable String Lengths in GA-Classifier |
| Chromosome Differentiation in VGA-Classifier |
| Multi-objective VGA-Classifier and Quantitative Indices |
| Genetic Algorithms in Clustering |
| Genetic Learning in Bioinformatics |
| Genetic Algorithms and Web Intelligence |
| Appendices |
| References |
| Index |
