Learning to Classify Text Using Support Vector Machines: 668 (The Springer International Series in Engineering and Computer Science) - Hardcover

Joachims, Thorsten

 
9780792376798: Learning to Classify Text Using Support Vector Machines: 668 (The Springer International Series in Engineering and Computer Science)
Hardcover
ISBN 10: 079237679X ISBN 13: 9780792376798
Verlag: Springer, 2002

Inhaltsangabe

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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Reseña del editor

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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Verlag
Springer
Erscheinungsdatum
2002
Sprache
Englisch
ISBN 10 
079237679X
ISBN 13 
9780792376798
Einband
Tapa dura
Anzahl der Seiten
228
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
CMN Printpool Inh. Mathis Neumann
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

Friedrich-Karl-Str. 9
Hamburg
Deutschland

Weitere beliebte Ausgaben desselben Titels

9781461352983: Learning to Classify Text Using Support Vector Machines: 668 (The Springer International Series in Engineering and Computer Science)

Vorgestellte Ausgabe

ISBN 10:  1461352983 ISBN 13:  9781461352983
Verlag: Springer, 2012
Softcover