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Grouping Multidimensional Data - Jacob Kogan#Charles Nicholas#Marc Teboulle
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Jacob Kogan#Charles Nicholas#Marc Teboulle:
Grouping Multidimensional Data - neues Buch

2006, ISBN: 9783540283492

ID: 689060895

Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection.Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as application and evaluation of algorithms, and thus provide an excellent state-of-the-art overview.The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas. Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection. Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data a eBooks > Fremdsprachige eBooks > Englische eBooks > Sach- & Fachthemen > Mathematik PDF 08.02.2006, Jacob Kogan#Charles Nicholas#Marc Teboulle, .200

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Grouping Multidimensional Data - Springer
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Springer:
Grouping Multidimensional Data - neues Buch

2006, ISBN: 9783540283492

ID: 689060895

Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection.Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as application and evaluation of algorithms, and thus provide an excellent state-of-the-art overview.The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas. Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection. Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data a eBooks > Fremdsprachige eBooks > Englische eBooks > Sach- & Fachthemen > Mathematik PDF 08.02.2006 eBook, Springer, .200

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Grouping Multidimensional Data - Recent Advances in Clustering - Kogan, Jacob; Nicholas, Charles; Teboulle, Marc
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Kogan, Jacob; Nicholas, Charles; Teboulle, Marc:
Grouping Multidimensional Data - Recent Advances in Clustering - neues Buch

2006, ISBN: 3540283498

ID: 9783540283492

In englischer Sprache. Verlag: Springer Berlin, Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection. Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as application and evaluation of algorithms, and thus provide an excellent state-of-the-art overview. The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas. PC-PDF, 268 Seiten, XII Seiten, 268 Seiten, [GR: 9632 - Nonbooks, PBS / Informatik, EDV/Informatik], [SW: - Informatik], [DRM: DE], [Ausgabe: 2006][PU:Springer Berlin], [PU: Springer, Berlin/Heidelberg]

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Grouping Multidimensional Data - Jacob Kogan; Charles Nicholas; Marc Teboulle
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Jacob Kogan; Charles Nicholas; Marc Teboulle:
Grouping Multidimensional Data - neues Buch

ISBN: 9783540283492

ID: 9783540283492

Computer Science; Data Structures, Cryptology and Information Theory; Information Storage and Retrieval; Statistical Theory and Methods; Math Applications in Computer Science; Statistics and Computing/Statistics Programs; Pattern Recognition Excel, LA, MATLAB, algorithms, classification, clustering algorithm, correlation, data analysis, data clustering, data mining, text clustering, text mining Books eBook, Springer Science+Business Media

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Grouping Multidimensional Data - Jacob Kogan; Charles Nicholas; Marc Teboulle
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Jacob Kogan; Charles Nicholas; Marc Teboulle:
Grouping Multidimensional Data - neues Buch

ISBN: 9783540283492

ID: 9783540283492

Computer Science; Data Structures, Cryptology and Information Theory; Information Storage and Retrieval; Statistical Theory and Methods; Math Applications in Computer Science; Statistics and Computing/Statistics Programs; Pattern Recognition Excel, LA, MATLAB, algorithms, classification, clustering algorithm, correlation, data analysis, data clustering, data mining, text clustering, text mining Books eBook, Springer Nature

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Detailangaben zum Buch - Grouping Multidimensional Data


EAN (ISBN-13): 9783540283492
ISBN (ISBN-10): 3540283498
Erscheinungsjahr: 2006
Herausgeber: Springer Berlin
268 Seiten
Sprache: eng/Englisch

Buch in der Datenbank seit 13.02.2007 04:29:06
Buch zuletzt gefunden am 13.11.2017 18:40:30
ISBN/EAN: 9783540283492

ISBN - alternative Schreibweisen:
3-540-28349-8, 978-3-540-28349-2


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