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Añadir al carritoHardcover. Condición: New. In shrink wrap. Looks like an interesting title!
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Añadir al carritoCondición: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
Publicado por Kluwer Academic Publishers, 2001
ISBN 10: 079237679X ISBN 13: 9780792376798
Librería: Librería Ofisierra, Galapagar, M, España
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Añadir al carritoHardcover. Good condition. Dog-eared corners. Libro.
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Librería: Books Puddle, New York, NY, Estados Unidos de America
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Añadir al carritoCondición: New. pp. 228.
Idioma: Inglés
Publicado por Kluwer Academic Publishers, 2002
ISBN 10: 079237679X ISBN 13: 9780792376798
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Añadir al carritoCondición: New. Based on ideas from Support Vector Machines (SVMs), this title presents an approach to generating text classifiers from examples. This book gives a detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, and, efficient performance estimation. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 205 pages, biography. BIC Classification: UYQM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 14. Weight in Grams: 498. . 2002. Hardback. . . . .
Idioma: Inglés
Publicado por Kluwer Academic Publishers, 2002
ISBN 10: 079237679X ISBN 13: 9780792376798
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 165,75
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Añadir al carritoCondición: New. Based on ideas from Support Vector Machines (SVMs), this title presents an approach to generating text classifiers from examples. This book gives a detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, and, efficient performance estimation. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 205 pages, biography. BIC Classification: UYQM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 14. Weight in Grams: 498. . 2002. Hardback. . . . . Books ship from the US and Ireland.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high performance and efficiency with theoretical understanding and improved robustness. In particular, it is highly effective without greedy heuristic components. The SVM approach is computationally efficient in training and classification, and it comes with a learning theory that can guide real-world applications.Learning To Classify Text Using Support Vector Machines gives a complete and detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, efficient performance estimation, and a statistical learning model of text classification. In addition, it includes an overview of the field of text classification, making it self-contained even for newcomers to the field. This book gives a concise introduction to SVMs for pattern recognition, and it includes a detailed description of how to formulate text-classification tasks for machine learning.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high performance and efficiency with theoretical understanding and improved robustness. In particular, it is highly effective without greedy heuristic components. The SVM approach is computationally efficient in training and classification, and it comes with a learning theory that can guide real-world applications.Learning To Classify Text Using Support Vector Machines gives a complete and detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, efficient performance estimation, and a statistical learning model of text classification. In addition, it includes an overview of the field of text classification, making it self-contained even for newcomers to the field. This book gives a concise introduction to SVMs for pattern recognition, and it includes a detailed description of how to formulate text-classification tasks for machine learning. 224 pp. Englisch.
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Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high performance and efficiency with .
Librería: Majestic Books, Hounslow, Reino Unido
EUR 147,06
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Añadir al carritoCondición: New. Print on Demand pp. 228 Illus.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 228.
Librería: preigu, Osnabrück, Alemania
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Añadir al carritoBuch. Condición: Neu. Learning to Classify Text Using Support Vector Machines | Thorsten Joachims | Buch | xvii | Englisch | 2002 | Springer | EAN 9780792376798 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Idioma: Inglés
Publicado por Springer, Springer Apr 2002, 2002
ISBN 10: 079237679X ISBN 13: 9780792376798
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high performance and efficiency with theoretical understanding and improved robustness. In particular, it is highly effective without greedy heuristic components. The SVM approach is computationally efficient in training and classification, and it comes with a learning theory that can guide real-world applications.Learning To Classify Text Using Support Vector Machines gives a complete and detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, efficient performance estimation, and a statistical learning model of text classification. In addition, it includes an overview of the field of text classification, making it self-contained even for newcomers to the field. This book gives a concise introduction to SVMs for pattern recognition, and it includes a detailed description of how to formulate text-classification tasks for machine learning.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 224 pp. Englisch.