Classification and Learning Using Genetic Algorithms : Applications in Bioinformatics and Web Intelligence /
By: Bandyopadhyay, Sanghamitra [author.].
Contributor(s): Pal, Sankar K [author.2] | SpringerLink (Online service)0.
Material type:
BookSeries: Natural Computing Series: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.Description: XVI, 311 p. 87 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540496076.Subject(s): Computer science | Computer programming | Artificial intelligence | Pattern recognition | Bioinformatics | Statistical physics | Dynamical systems | Electrical engineering.1 | Computer Science.2 | Pattern Recognition.2 | Programming Techniques.2 | Communications Engineering, Networks.2 | Artificial Intelligence (incl. Robotics).2 | Statistical Physics, Dynamical Systems and Complexity.2 | Computational Biology/Bioinformatics.1DDC classification: 006.4 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
| PK Kelkar Library, IIT Kanpur | Available | EBK1545 |
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.
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-�-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. This book will be useful to graduate students and researchers in computer science, electrical engineering, systems science, and information technology, both as a text and reference book. Researchers and practitioners in industry working in system design, control, pattern recognition, data mining, soft computing, bioinformatics and Web intelligence will also benefit.
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