Cargando…

Classification and Learning Using Genetic Algorithms Applications in Bioinformatics 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...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Bandyopadhyay, Sanghamitra (Autor), Pal, Sankar Kumar (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2007.
Edición:1st ed. 2007.
Colección:Natural Computing Series,
Temas:
Acceso en línea:Texto Completo

MARC

LEADER 00000nam a22000005i 4500
001 978-3-540-49607-6
003 DE-He213
005 20230719195940.0
007 cr nn 008mamaa
008 100301s2007 gw | s |||| 0|eng d
020 |a 9783540496076  |9 978-3-540-49607-6 
024 7 |a 10.1007/3-540-49607-6  |2 doi 
050 4 |a Q337.5 
050 4 |a TK7882.P3 
072 7 |a UYQP  |2 bicssc 
072 7 |a COM016000  |2 bisacsh 
072 7 |a UYQP  |2 thema 
082 0 4 |a 006.4  |2 23 
100 1 |a Bandyopadhyay, Sanghamitra.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Classification and Learning Using Genetic Algorithms  |h [electronic resource] :  |b Applications in Bioinformatics and Web Intelligence /  |c by Sanghamitra Bandyopadhyay, Sankar Kumar Pal. 
250 |a 1st ed. 2007. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2007. 
300 |a XVI, 311 p. 87 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Natural Computing Series,  |x 2627-6461 
505 0 |a 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. 
520 |a 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. 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. 
650 0 |a Pattern recognition systems. 
650 0 |a Computer programming. 
650 0 |a Telecommunication. 
650 0 |a Artificial intelligence. 
650 0 |a System theory. 
650 0 |a Bioinformatics. 
650 1 4 |a Automated Pattern Recognition. 
650 2 4 |a Programming Techniques. 
650 2 4 |a Communications Engineering, Networks. 
650 2 4 |a Artificial Intelligence. 
650 2 4 |a Complex Systems. 
650 2 4 |a Computational and Systems Biology. 
700 1 |a Pal, Sankar Kumar.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783540833239 
776 0 8 |i Printed edition:  |z 9783642080548 
776 0 8 |i Printed edition:  |z 9783540496069 
830 0 |a Natural Computing Series,  |x 2627-6461 
856 4 0 |u https://doi.uam.elogim.com/10.1007/3-540-49607-6  |z Texto Completo 
912 |a ZDB-2-SCS 
912 |a ZDB-2-SXCS 
950 |a Computer Science (SpringerNature-11645) 
950 |a Computer Science (R0) (SpringerNature-43710)