Isbn: 9780471681823 - learning from data: concepts, theory, and methods (ieee press) (27 resultados)

Condición: Good. Good condition. 2nd edition. A copy that has been read but remains intact. May contain markings such as bookplates, stamps, limited notes and highlighting, or a few light stains.

Hardcover. Condición: Very Good. 2. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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Hardcover. Condición: Good. No Jacket. Former library book; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Condición: acceptable. Used - Acceptable: All pages and the cover are intact, but shrink wrap, dust covers, or boxed set case may be missing. Pages may include limited notes, highlighting, or minor water damage but the text is readable. Pages may include limited notes and highlighting, but the text cannot be obscured or unreadable. Any access codes or passwords originally included with the book may be expired, used or no longer valid. Image is stock photo and cover art edition may be different than pictured.…

Hardcover. Condición: Gut. Second edition. 560 pp. Cover sun-bleached at spine, otherwise very well preserved copy 324 Sprache: Englisch Gewicht in Gramm: 1200.

hardcover. Condición: Gut. 560 Seiten; 9780471681823.3 Gewicht in Gramm: 1.

Condición: As New. Unread book in perfect condition.

Condición: new.

Condición: New.

HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

Condición: As New. Unread book in perfect condition.

Hardcover. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condición: New.

Condición: New. pp. xviii + 538 Illus.

Condición: New. In English.

Condición: New. An interdisciplinary framework for learning methodologies, covering statistics, neural networks, and fuzzy logic, Learning from Data provides a unified treatment of the principles and methods for learning dependencies from data. Num Pages: 538 pages, Illustrations. BIC Classification: UYQM. Category: (P) Professional & Vocational. Dimension: 244 x 157 x 38. Weight in Grams: 906. . 2007. 2nd Edition. Hardcover. . . . .…

Condición: New. pp. xviii + 538 2nd Edition.

Condición: New. Vladimir CherKassky, PhD, is Professor of Electrical and Computer Engineering at the University of Minnesota. He is internationally known for his research on neural networks and statistical learning.Filip Mulier, PhD, has worked in the software field for th.

Hardcover. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Hardcover. Condición: Brand New. 2nd edition. 538 pages. 9.75x6.50x1.25 inches. In Stock.

Condición: New. An interdisciplinary framework for learning methodologies, covering statistics, neural networks, and fuzzy logic, Learning from Data provides a unified treatment of the principles and methods for learning dependencies from data. Num Pages: 538 pages, Illustrations. BIC Classification: UYQM. Category: (P) Professional & Vocational. Dimension: 244 x 157 x 38. Weight in Grams: 906. . 2007. 2nd Edition. Hardcover. . . . . Books ship from the US and Ireland.…

Buch. Condición: Neu. Neuware - An interdisciplinary framework for learning methodologies-now revised and updatedLearning from Data provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and pattern recognition can be applied-showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science.Since the first edition was published, the field of data-driven learning has experienced rapid growth. This Second Edition covers these developments with a completely revised chapter on support vector machines, a new chapter on noninductive inference and alternative learning formulations, and an in-depth discussion of the VC theoretical approach as it relates to other paradigms.Complete with over one hundred illustrations, case studies, examples, and chapter summaries, Learning from Data accommodates both beginning and advanced graduate students in engineering, computer science, and statistics. It is also indispensable for researchers and practitioners in these areas who must understand the principles and methods for learning dependencies from data.…

Hardcover. Condición: Brand New. 2nd edition. 538 pages. 9.75x6.50x1.25 inches. In Stock. This item is printed on demand.

Hardcover. Condición: new. Hardcover. An interdisciplinary framework for learning methodologiescovering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be appliedshowing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text. An interdisciplinary framework for learning methodologies, covering statistics, neural networks, and fuzzy logic, Learning from Data provides a unified treatment of the principles and methods for learning dependencies from data. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condición: New. PRINT ON DEMAND pp. xviii + 538.