Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases: 98 (Studies in Computational Intelligence) - Tapa blanda

9783642096150: Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases: 98 (Studies in Computational Intelligence)

Tapa blanda

ISBN 10: 3642096158 ISBN 13: 9783642096150

Editorial: Springer, 2010

Ver todas las copias de esta edici�n del ISBN

1 Usado

De EUR 165,71

11 Nuevo

De EUR 92,27

The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.

"Sinopsis" puede pertenecer a otra edici�n de este libro.

De la contraportada

Data Mining (DM) is the most commonly used name to describe such computational analysis of data and the results obtained must conform to several objectives such as accuracy, comprehensibility, interest for the user etc. Though there are many sophisticated techniques developed by various interdisciplinary fields only a few of them are well equipped to handle these multi-criteria issues of DM. Therefore, the DM issues have attracted considerable attention of the well established multiobjective genetic algorithm community to optimize the objectives in the tasks of DM.

"Sobre este t�tulo" puede pertenecer a otra edici�n de este libro.

EditorialSpringer
A�o de publicaci�n2010
ISBN 10 3642096158
ISBN 13 9783642096150
Encuadernaci�nTapa blanda
IdiomaIngl�s
N�mero de p�ginas176
EditorGhosh Ashish, Dehuri Satchidananda, Ghosh Susmita
Contacto del fabricanteno disponible

Comprar usado

Condici�n: Como Nuevo

Like New

Ver este art�culo

EUR 165,71

Convertir moneda

EUR 29,36 gastos de env�o desde Reino Unido a Espa�a

Destinos, gastos y plazos de env�o

A�adir al carrito

Comprar nuevo

Ver este art�culo

EUR 92,27

Convertir moneda

EUR 19,49 gastos de env�o desde Alemania a Espa�a

Destinos, gastos y plazos de env�o

A�adir al carrito

Otras ediciones populares con el mismo t�tulo

9783540774662: Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases: 98 (Studies in Computational Intelligence)

Edici�n Destacada

ISBN 10: 3540774661 ISBN 13: 9783540774662
Editorial: Springer, 2008
Tapa dura

Springer, 2008 (Tapa blanda)

Resultados de la b�squeda para Multi-Objective Evolutionary Algorithms for Knowledge...

Imagen del vendedor

Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases

Ghosh, Ashish|Dehuri, Satchidananda|Ghosh, Susmita

Publicado por Springer Berlin Heidelberg, 2010

ISBN 10: 3642096158 ISBN 13: 9783642096150

Nuevo Tapa blanda

Impresi�n bajo demanda

Librería: moluna, Greven, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Condici�n: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Assembles high quality original contributions that reflect and advance the state-of-the art in the area of Multi-objective Evolutionary Algorithms for Data Mining and Knowledge DiscoveryEmphasizes on the utility of evolutionary algorithms to vario. N� de ref. del art�culo: 5048619

Contactar al vendedor

Comprar nuevo

EUR 92,27

Convertir moneda

Gastos de env�o: EUR 19,49

De Alemania a Espa�a

Destinos, gastos y plazos de env�o

Cantidad disponible: M�s de 20 disponibles

A�adir al carrito

Imagen del vendedor

Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases

Ashish Ghosh

Publicado por Springer Berlin Heidelberg Nov 2010, 2010

ISBN 10: 3642096158 ISBN 13: 9783642096150

Nuevo Taschenbuch

Impresi�n bajo demanda

Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases. 176 pp. Englisch. N� de ref. del art�culo: 9783642096150

Contactar al vendedor

Comprar nuevo

EUR 106,99

Convertir moneda

Gastos de env�o: EUR 11,00

De Alemania a Espa�a

Destinos, gastos y plazos de env�o

Cantidad disponible: 2 disponibles

A�adir al carrito

Imagen del vendedor

Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases

Ashish Ghosh

Publicado por Springer Berlin Heidelberg, 2010

ISBN 10: 3642096158 ISBN 13: 9783642096150

Nuevo Taschenbuch

Librería: AHA-BUCH GmbH, Einbeck, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: Neu. Druck auf Anfrage Neuware - Printed after ordering - Data Mining (DM) is the most commonly used name to describe such computational analysis of data and the results obtained must conform to several objectives such as accuracy, comprehensibility, interest for the user etc. Though there are many sophisticated techniques developed by various interdisciplinary fields only a few of them are well equipped to handle these multi-criteria issues of DM. Therefore, the DM issues have attracted considerable attention of the well established multiobjective genetic algorithm community to optimize the objectives in the tasks of DM.The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases. N� de ref. del art�culo: 9783642096150

Contactar al vendedor

Comprar nuevo

EUR 106,99

Convertir moneda

Gastos de env�o: EUR 11,99

De Alemania a Espa�a

Destinos, gastos y plazos de env�o

Cantidad disponible: 1 disponibles

A�adir al carrito

Imagen de archivo

Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases (Studies in Computational Intelligence, 98)

Publicado por Springer, 2010

ISBN 10: 3642096158 ISBN 13: 9783642096150

Nuevo Tapa blanda

Librería: California Books, Miami, FL, Estados Unidos de America

Calificaci�n del vendedor: 5 de 5 estrellas

Condici�n: New. N� de ref. del art�culo: I-9783642096150

Contactar al vendedor

Comprar nuevo

EUR 127,81

Convertir moneda

Gastos de env�o: EUR 6,89

De Estados Unidos de America a Espa�a

Destinos, gastos y plazos de env�o

Cantidad disponible: M�s de 20 disponibles

A�adir al carrito

Imagen del vendedor

Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases

Ashish Ghosh

Publicado por Springer Berlin Heidelberg, Springer Berlin Heidelberg Nov 2010, 2010

ISBN 10: 3642096158 ISBN 13: 9783642096150

Nuevo Taschenbuch

Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: Neu. Neuware -Data Mining (DM) is the most commonly used name to describe such computational analysis of data and the results obtained must conform to several objectives such as accuracy, comprehensibility, interest for the user etc. Though there are many sophisticated techniques developed by various interdisciplinary fields only a few of them are well equipped to handle these multi-criteria issues of DM. Therefore, the DM issues have attracted considerable attention of the well established multiobjective genetic algorithm community to optimize the objectives in the tasks of DM.The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 176 pp. Englisch. N� de ref. del art�culo: 9783642096150

Contactar al vendedor