Learning to Classify Text Using Support Vector Machines

Thorsten Joachims

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Language: English

Published by Springer, Springer Nov 2012, 2012

1461352983 / 9781461352983

Series: Book 158 of 260 - The Springer International Series in Engineering and Computer Science

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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 228 pp. Englisch.

Seller Inventory # 9781461352983

Title
Learning to Classify Text Using Support Vector Machines
Author
Thorsten Joachims
Publisher
Springer, Springer Nov 2012
Publication year
2012
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
1461352983
ISBN 13
9781461352983
Item weight
353 grams
Dimensions
235x155x13 mm
Series
Book 158 of 260: The Springer International Series in Engineering and Computer Science

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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