Learning to Classify Text Using Support Vector Machines by Thorsten Joachims

Learning to Classify Text Using Support Vector Machines by Thorsten Joachims

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.

SKU	Non disponible
ISBN 13	9780792376798
ISBN 10	079237679X
Titre	Learning to Classify Text Using Support Vector Machines
Auteur	Thorsten Joachims
Série	The Springer International Series In Engineering And Computer Science
État	Non disponible
Type de reliure	Hardback
Éditeur	Kluwer Academic Publishers
Année de publication	2002-04-30
Nombre de pages	205
Note de couverture	La photo du livre est présentée à titre d'illustration uniquement. La reliure, la couverture ou l'édition réelle peuvent varier.
Note	Non disponible