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In den WarenkorbZustand: New. pp. 221.
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In den WarenkorbHardcover. Zustand: New.
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In den WarenkorbZustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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In den WarenkorbZustand: New. pp. 176 Illus.
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In den WarenkorbPaperback. Zustand: Brand New. 132 pages. 9.25x6.10x0.31 inches. In Stock.
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In den WarenkorbZustand: New. In.
Verlag: World Scientific Publishing Co Pte Ltd, 2011
ISBN 10: 9814280143 ISBN 13: 9789814280143
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: New. ---. nein.
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Verlag: World Scientific Publishing Company, 2011
ISBN 10: 9814280143 ISBN 13: 9789814280143
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Verlag: Springer Nature Singapore, 2020
ISBN 10: 9811577811 ISBN 13: 9789811577819
Sprache: Englisch
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In den WarenkorbZustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher.
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Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg Nov 2010, 2010
ISBN 10: 3642096158 ISBN 13: 9783642096150
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: 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.
Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg Mär 2008, 2008
ISBN 10: 3540774661 ISBN 13: 9783540774662
Sprache: Englisch
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In den WarenkorbBuch. Zustand: 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.
Verlag: Springer Berlin Heidelberg, 2010
ISBN 10: 3642096158 ISBN 13: 9783642096150
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 106,99
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In den WarenkorbTaschenbuch. Zustand: 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.
Verlag: Springer Berlin Heidelberg, 2008
ISBN 10: 3540774661 ISBN 13: 9783540774662
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 106,99
Währung umrechnenAnzahl: 1 verfügbar
In den WarenkorbBuch. Zustand: 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.
Verlag: Springer Berlin Heidelberg, 2008
ISBN 10: 3642096158 ISBN 13: 9783642096150
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: Brand New. 174 pages. 9.21x6.06x0.47 inches. In Stock.
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In den WarenkorbZustand: New. In.
Verlag: World Scientific Pub Co Inc, 2011
ISBN 10: 9814280143 ISBN 13: 9789814280143
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 352 pages. 9.25x6.25x1.25 inches. In Stock.
Verlag: Springer Berlin Heidelberg, 2012
ISBN 10: 3642260535 ISBN 13: 9783642260537
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The purpose of this book is to collect contributions that are at the intersection of multi-objective optimization, swarm intelligence (specifically, particle swarm optimization and ant colony optimization) and data mining. Such a collection intends to illustrate the potential of multi-objective swarm intelligence techniques in data mining, with the aim of motivating more researchers in evolutionary computation and machine learning to do research in this field. This volume consists of eleven chapters, including an introduction that provides the basic concepts of swarm intelligence techniques and a discussion of their use in data mining. Some of the research challenges that must be faced when using swarm intelligence techniques in data mining are also addressed. The rest of the chapters were contributed by leading researchers, and were organized according to the steps normally followed in Knowledge Discovery in Databases (KDD) (i.e., data preprocessing, data mining, and post processing).We hope that this book becomes a valuable reference for those wishing to do research on the use of multi-objective swarm intelligence techniques in data mining and knowledge discovery in databases.
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In den WarenkorbPaperback. Zustand: Brand New. 374 pages. 9.25x6.10x0.78 inches. In Stock.
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In den WarenkorbHardcover. Zustand: Brand New. 374 pages. 9.25x6.10x0.88 inches. In Stock.