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9780792376798 - Learning to Classify Text Using Support Vector Machines: Methods, Theory, and Algorithms: 668 di Joachims, Thorsten (19 risultati)
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Learning to Classify Text Using Support Vector Machines (The Springer International Series in Engineering and Computer Science, 668)
Libro 158 di 260: The Springer International Series in Engineering and Computer ScienceDa: BennettBooksLtd, Los Angeles, CA, U.S.A.
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Hardcover. Condizione: New. In shrink wrap. Looks like an interesting title!
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Learning to Classify Text Using Support Vector Machines (The Springer International Series in Engineering and Computer Science, 668)
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Aggiungi al carrelloCondizione: 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.
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Learning to Classify Text Using Support Vector Machines. Methods, Theory and Algorithms
Editore: Kluwer Academic Publishers, 2001
ISBN 10: 079237679X ISBN 13: 9780792376798
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Aggiungi al carrelloHardcover. Good condition. Dog-eared corners. Libro.
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Learning to Classify Text Using Support Vector Machines (The Springer International Series in Engineering and Computer Science, 668)
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Learning to Classify Text Using Support Vector Machines : Methods, Theory, and Algorithms
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Learning to Classify Text Using Support Vector Machines : Methods, Theory, and Algorithms
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Learning to Classify Text Using Support Vector Machines
Libro 158 di 260: The Springer International Series in Engineering and Computer ScienceDa: Books Puddle, New York, NY, U.S.A.
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Learning to Classify Text Using Support Vector Machines
Libro 158 di 260: The Springer International Series in Engineering and Computer ScienceLingua: Inglese
Editore: Kluwer Academic Publishers, 2002
ISBN 10: 079237679X ISBN 13: 9780792376798
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Aggiungi al carrelloCondizione: 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. . . . .
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Learning to Classify Text Using Support Vector Machines
Libro 158 di 260: The Springer International Series in Engineering and Computer ScienceLingua: Inglese
Editore: Kluwer Academic Publishers, 2002
ISBN 10: 079237679X ISBN 13: 9780792376798
Da: Kennys Bookstore, Olney, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: 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.
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Learning to Classify Text Using Support Vector Machines
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Aggiungi al carrelloBuch. Condizione: 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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Learning to Classify Text Using Support Vector Machines : Methods, Theory, and Algorithms
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
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Learning to Classify Text Using Support Vector Machines (The Springer International Series in Engineering and Computer Science (668))
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Aggiungi al carrelloHardcover. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Learning to Classify Text Using Support Vector Machines : Methods, Theory, and Algorithms
Libro 158 di 260: The Springer International Series in Engineering and Computer ScienceDa: GreatBookPrices, Columbia, MD, U.S.A.
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Learning to Classify Text Using Support Vector Machines
Libro 158 di 260: The Springer International Series in Engineering and Computer ScienceDa: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Aggiungi al carrelloBuch. Condizione: 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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Learning to Classify Text Using Support Vector Machines
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Aggiungi al carrelloGebunden. Condizione: 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 .
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Learning to Classify Text Using Support Vector Machines
Libro 158 di 260: The Springer International Series in Engineering and Computer ScienceDa: Majestic Books, Hounslow, Regno Unito
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Aggiungi al carrelloCondizione: New. Print on Demand pp. 228 Illus.
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Learning to Classify Text Using Support Vector Machines
Libro 158 di 260: The Springer International Series in Engineering and Computer ScienceDa: Biblios, Frankfurt am main, HESSE, Germania
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 228.
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Learning to Classify Text Using Support Vector Machines
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Aggiungi al carrelloBuch. Condizione: 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.
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Learning to Classify Text Using Support Vector Machines
Libro 158 di 260: The Springer International Series in Engineering and Computer ScienceLingua: Inglese
Editore: Springer, Springer Apr 2002, 2002
ISBN 10: 079237679X ISBN 13: 9780792376798
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloBuch. Condizione: 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.
