Kniha Learning to Classify Text Using Support Vector Machines Thorsten Joachims

Learning to Classify Text Using Support Vector Machines

Methods, Theory and Algorithms

Jazyk: Angličtina
Vazba: Pevná
Vydavatel: Springer
Dostupnost: Skladem u dodavatele
Odesíláme za 10-13 dnů
2 286
Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector M...

Informace o knize

Jazyk
Angličtina
Vazba
Kniha - Pevná
Vydáno
2002
Stránek
205
EAN
9780792376798
ISBN
079237679X
Enbook ID
01397195
Vydavatel
Hmotnost
1100
Rozměry
155 x 235 x 17

Kompletní popis

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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