Learning to Classify Text Using Support Vector Machines

Name: Learning to Classify Text Using Support Vector Machines
Brand: Springer, Berlin
SKU: 9781461352983
Price: 2286 CZK
Availability: InStock

Autor: Thorsten Joachims

Jazyk:

Vazba: Brožovaná

Vydavatel: Springer, Berlin

Dostupnost: Skladem u dodavatele

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2 286 Kč

Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector M...

Informace o knize

Autor

Thorsten Joachims

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2013

Stránek

205

EAN

9781461352983

ISBN

1461352983

Enbook ID

06796280

Vydavatel

Springer, Berlin

Hmotnost

355

Rozměry

155 x 235 x 12

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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