Sprache: Englisch
Verlag: Society for Industrial and Appli, 2007
ISBN 10: 0898716268 ISBN 13: 9780898716269
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Paperback. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Sprache: Englisch
Verlag: Society for Industrial and Applied Mathematics, 2007
ISBN 10: 0898716268 ISBN 13: 9780898716269
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Sprache: Englisch
Verlag: SIAM - Society for Industrial and Applied Mathematics, 2019
ISBN 10: 1611975859 ISBN 13: 9781611975857
Anbieter: Bay State Book Company, North Smithfield, RI, USA
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Sprache: Englisch
Verlag: Society for Industrial and Applied Mathematics, 2007
ISBN 10: 0898716268 ISBN 13: 9780898716269
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
Sprache: Englisch
Verlag: SIAM - Society for Industrial and Applied Mathematics, 2019
ISBN 10: 1611975859 ISBN 13: 9781611975857
Anbieter: Brook Bookstore On Demand, Napoli, NA, Italien
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Tapa Blanda. Zustand: Bien. Tapa blanda. Abundantes gráficos e ilustraciones.9780898716269. Siam. Estados Unidos. 2007. 26x18 centímetros. 224 páginas. Tapa blanda. Estado=Bien. Inglés.
Sprache: Englisch
Verlag: Society for Industrial and Applied Mathematics,U.S., US, 2020
ISBN 10: 1611975859 ISBN 13: 9781611975857
Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes Königreich
EUR 78,50
Anzahl: 2 verfügbar
In den WarenkorbPaperback. Zustand: New. Second Edition. This thoroughly revised second edition provides an updated treatment of numerical linear algebra techniques for solving problems in data mining and pattern recognition. Adopting an application-oriented approach, the author introduces matrix theory and decompositions, describes how modern matrix methods can be applied in real life scenarios, and provides a set of tools that students can modify for a particular application.Building on material from the first edition, the author discusses basic graph concepts and their matrix counterparts. He introduces the graph Laplacian and properties of its eigenvectors needed in spectral partitioning and describes spectral graph partitioning applied to social networks and text classification. Examples are included to help readers visualize the results. This new edition also presents matrix-based methods that underlie many of the algorithms used for big data.The book provides a solid foundation to further explore related topics and presents applications such as classification of handwritten digits, text mining, text summarization, PageRank computations related to the Google search engine, and facial recognition. Exercises and computer assignments are available on a Web page that supplements the book.Matrix Methods in Data Mining and Pattern Recognition, Second Edition is primarily for undergraduate students who have previously taken an introductory scientific computing/numerical analysis course and graduate students in data mining and pattern recognition areas who need an introduction to linear algebra techniques.
Sprache: Englisch
Verlag: SIAM - Society for Industrial and Applied Mathematics, 2019
ISBN 10: 1611975859 ISBN 13: 9781611975857
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. 2nd revised edition edition. 229 pages. 10.00x7.05x0.63 inches. In Stock.
Sprache: Englisch
Verlag: SIAM - Society for Industrial and Applied Mathematics, 2019
ISBN 10: 1611975859 ISBN 13: 9781611975857
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
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Sprache: Englisch
Verlag: Society for Industrial & Applied Mathematics,U.S., 2019
ISBN 10: 1611975859 ISBN 13: 9781611975857
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In den WarenkorbPaperback / softback. Zustand: New. New copy - Usually dispatched within 4 working days.
Sprache: Englisch
Verlag: SIAM - Society for Industrial and Applied Mathematics, 2019
ISBN 10: 1611975859 ISBN 13: 9781611975857
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Zustand: New. 2019. Second. paperback. . . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: SIAM - Society for Industrial and Applied Mathematics, 2019
ISBN 10: 1611975859 ISBN 13: 9781611975857
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. Second edition NO-PA16APR2015-KAP.
Sprache: Englisch
Verlag: Society for Industrial and Applied Mathematics, 2007
ISBN 10: 0898716268 ISBN 13: 9780898716269
Anbieter: BennettBooksLtd, Los Angeles, CA, USA
paperback. Zustand: New. In shrink wrap. Looks like an interesting title!
Sprache: Englisch
Verlag: Society for Industrial and Applied Mathematics, 2007
ISBN 10: 0898716268 ISBN 13: 9780898716269
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 107,44
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In den WarenkorbZustand: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
Sprache: Englisch
Verlag: Society for Industrial and Applied Mathematics,U.S., US, 2020
ISBN 10: 1611975859 ISBN 13: 9781611975857
Anbieter: Rarewaves.com UK, London, Vereinigtes Königreich
EUR 74,25
Anzahl: 2 verfügbar
In den WarenkorbPaperback. Zustand: New. Second Edition. This thoroughly revised second edition provides an updated treatment of numerical linear algebra techniques for solving problems in data mining and pattern recognition. Adopting an application-oriented approach, the author introduces matrix theory and decompositions, describes how modern matrix methods can be applied in real life scenarios, and provides a set of tools that students can modify for a particular application.Building on material from the first edition, the author discusses basic graph concepts and their matrix counterparts. He introduces the graph Laplacian and properties of its eigenvectors needed in spectral partitioning and describes spectral graph partitioning applied to social networks and text classification. Examples are included to help readers visualize the results. This new edition also presents matrix-based methods that underlie many of the algorithms used for big data.The book provides a solid foundation to further explore related topics and presents applications such as classification of handwritten digits, text mining, text summarization, PageRank computations related to the Google search engine, and facial recognition. Exercises and computer assignments are available on a Web page that supplements the book.Matrix Methods in Data Mining and Pattern Recognition, Second Edition is primarily for undergraduate students who have previously taken an introductory scientific computing/numerical analysis course and graduate students in data mining and pattern recognition areas who need an introduction to linear algebra techniques.
Sprache: Englisch
Verlag: Society for Industrial and Applied Mathematics, 2007
ISBN 10: 0898716268 ISBN 13: 9780898716269
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