Classification and Learning Using Genetic Algorithms. Applications in Bioinformatics and Web Intelligence
By Sanghamitra Bandyopadhyay, Sankar K. Pal,
Publisher: Springer
Number Of Pages: 311
Publication Date: 2007-05
Sales Rank: 1569142
ISBN / ASIN: 3540496068
EAN: 9783540496069
Binding: Hardcover
Manufacturer: Springer
Studio: Springer
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-脿-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.
Filetype: RARed PDF
Password: none
Filesize: 6.977.436 Bytes
http://rapidshare.com/files/63702225/nnbioinf.rar
By Sanghamitra Bandyopadhyay, Sankar K. Pal,
Publisher: Springer
Number Of Pages: 311
Publication Date: 2007-05
Sales Rank: 1569142
ISBN / ASIN: 3540496068
EAN: 9783540496069
Binding: Hardcover
Manufacturer: Springer
Studio: Springer
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-脿-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.
Filetype: RARed PDF
Password: none
Filesize: 6.977.436 Bytes
http://rapidshare.com/files/63702225/nnbioinf.rar
