"Learning to Classify Text Using Support Vector Machines" - Information and Links:

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The cover of “Learning to Classify Text Using Support Vector Machines” - Open Library.

"Learning to Classify Text Using Support Vector Machines" was published by Springer US in 2002 - Boston, MA, it has 205 pages and the language of the book is English.


“Learning to Classify Text Using Support Vector Machines” Metadata:

  • Title: ➤  Learning to Classify Text Using Support Vector Machines
  • Author:
  • Language: English
  • Number of Pages: 205
  • Publisher: Springer US
  • Publish Date:
  • Publish Location: Boston, MA

“Learning to Classify Text Using Support Vector Machines” Subjects and Themes:

Edition Specifications:

  • Format: [electronic resource] /
  • Pagination: ➤  1 online resource (xvii, 205 pages).

Edition Identifiers:

AI-generated Review of “Learning to Classify Text Using Support Vector Machines”:


"Learning to Classify Text Using Support Vector Machines" Description:

The Open Library:

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.

Open Data:

LEARNING TO CLASSIFY TEXT USING SUPPORT VECTOR MACHINES -- Copyright -- Contents -- Foreword -- Preface -- Acknowledgments -- Notation -- Chapter 1 INTRODUCTION -- Chapter 2 TEXT CLASSIFICATION -- Chapter 3 SUPPORT VECTOR MACHINES -- Chapter 4 A STATISTICAL LEARNING MODEL OF TEXT CLASSIFICATION FOR SVMS -- Chapter 5 EFFICIENT PERFORMANCE ESTIMATORS FOR SVMS -- Chapter 6 INDUCTIVE TEXT CLASSIFICATION -- Chapter 7 TRANSDUCTIVE TEXT CLASSIFICATION -- Chapter 8 TRAINING INDUCTIVE SUPPORT VECTOR MACHINES -- Chapter 9 TRAINING TRANSDUCTIVE SUPPORT VECTOR MACHINES -- Chapter 10 CONCLUSIONS -- References -- Appendix A SVM-Light Commands and Options -- Index

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