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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Foreword; T.Mitchell, K. Morik. Preface. Acknowledgments. Notation. 1. Introduction. 2. Text Classification. 3. Support Vector Machines. Part Theory. 4. A Statistical Learning Model of Text Classification for SVMS. 5. Efficient Performance Estimators for SVMS. Part Methods. 6. Inductive Text Classification. 7. Transductive Text Classification. Part Algorithms. 8. Training Inductive Support Vector Machines. 9. Training Transductive Support Vector Machines. 10. Conclusions. Bibliography. Appendices. Index.
Book by Joachims Thorsten
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
EUR 6,90 per la spedizione da U.S.A. a Italia
Destinazione, tempi e costiEUR 23,61 per la spedizione da U.S.A. a Italia
Destinazione, tempi e costiDa: ThriftBooks-Dallas, Dallas, TX, U.S.A.
Hardcover. Condizione: Good. No Jacket. Former library book; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 1.05. Codice articolo G079237679XI3N10
Quantità: 1 disponibili
Da: Ammareal, Morangis, Francia
Hardcover. Condizione: Très bon. Ancien livre de bibliothèque avec équipements. Edition 2002. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 2002. Ammareal gives back up to 15% of this item's net price to charity organizations. Codice articolo G-122-170
Quantità: 1 disponibili
Da: Librería Ofisierra, Galapagar, M, Spagna
Hardcover. Good condition. Dog-eared corners. Libro. Codice articolo 146893
Quantità: 1 disponibili
Da: Better World Books: West, Reno, NV, U.S.A.
Condizione: Very Good. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects. Codice articolo 52072873-75
Quantità: 1 disponibili
Da: Magus Books Seattle, Seattle, WA, U.S.A.
Hardcover. Condizione: VG. used hardcover copy in illustrated boards, no jacket, as issued. light shelfwear, corners perhaps slightly bumped. pages and binding are clean, straight and tight. there are no marks to the text or other serious flaws. Codice articolo 1188352
Quantità: 1 disponibili
Da: Shakespeare Book House, Rockford, IL, U.S.A.
Condizione: New. The item is Brand New! Codice articolo 570TQW0008NH_ns
Quantità: 1 disponibili
Da: moluna, Greven, Germania
Gebunden. 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 . Codice articolo 5970343
Quantità: Più di 20 disponibili
Da: BennettBooksLtd, North Las Vegas, NV, U.S.A.
Hardcover. Condizione: New. In shrink wrap. Looks like an interesting title! Codice articolo Q-079237679X
Quantità: 1 disponibili
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Buch. 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. Codice articolo 9780792376798
Quantità: 2 disponibili
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Buch. Condizione: Neu. 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 224 pp. Englisch. Codice articolo 9780792376798
Quantità: 2 disponibili