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Condition: New. Well packaged and promptly shipped from California. Partnered with Friends of the Library since 2010.
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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases (Studies in Computational Intelligence, 98, Band 98)
Seller: Leserstrahl (Preise inkl. MwSt.), Oldenbüttel, Germany
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Condition: New. pp. 176.
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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases (Studies in Computational Intelligence, 98)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Published by Springer Berlin Heidelberg, 2010
ISBN 10: 3642096158 ISBN 13: 9783642096150
Language: English
US$ 127.30
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Add to basketTaschenbuch. Condition: 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.
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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Published by Springer Berlin Heidelberg, 2008
ISBN 10: 3540774661 ISBN 13: 9783540774662
Language: English
US$ 127.30
Convert currencyUS$ 34.85 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketBuch. Condition: 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.
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Condition: New. pp. 176.
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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases (Studies in Computational Intelligence, 98)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases (Studies in Computational Intelligence)
Published by Springer Berlin Heidelberg, 2008
ISBN 10: 3642096158 ISBN 13: 9783642096150
Language: English
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Add to basketPaperback. Condition: Brand New. 174 pages. 9.21x6.06x0.47 inches. In Stock.
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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg Nov 2010, 2010
ISBN 10: 3642096158 ISBN 13: 9783642096150
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
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Add to basketTaschenbuch. Condition: 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.
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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg Mär 2008, 2008
ISBN 10: 3540774661 ISBN 13: 9783540774662
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
US$ 127.30
Convert currencyUS$ 63.53 shipping from Germany to U.S.A.Quantity: 2 available
Add to basketBuch. Condition: 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.
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US$ 191.63
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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Published by Springer Berlin Heidelberg Mrz 2008, 2008
ISBN 10: 3540774661 ISBN 13: 9783540774662
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
US$ 127.30
Convert currencyUS$ 26.57 shipping from Germany to U.S.A.Quantity: 2 available
Add to basketBuch. Condition: 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.
-
Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Published by Springer Berlin Heidelberg Nov 2010, 2010
ISBN 10: 3642096158 ISBN 13: 9783642096150
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
US$ 127.30
Convert currencyUS$ 26.57 shipping from Germany to U.S.A.Quantity: 2 available
Add to basketTaschenbuch. Condition: 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.
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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Published by Springer Berlin Heidelberg, 2010
ISBN 10: 3642096158 ISBN 13: 9783642096150
Language: English
US$ 109.79
Convert currencyUS$ 56.59 shipping from Germany to U.S.A.Quantity: Over 20 available
Add to basketCondition: 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.
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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Published by Springer Berlin Heidelberg, 2008
ISBN 10: 3540774661 ISBN 13: 9783540774662
Language: English
US$ 109.79
Convert currencyUS$ 56.59 shipping from Germany to U.S.A.Quantity: Over 20 available
Add to basketCondition: 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.
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US$ 174.13
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Add to basketCondition: New. Print on Demand pp. 176 67 Illus.
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Add to basketCondition: New. PRINT ON DEMAND pp. 176.
