bookApr 1, 2002Closed access
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Abstract
Foreword T.Mitchell, K. Morik. Preface. Acknowledgments. Notation. 1. Introduction. 2. Text Classification. 3. Support Vector Machines. Part Theory. 4. A Statistical Learning Model of Text Classification for SVMS. 5. Efficient Performance Estimators for SVMS. Part Methods. 6. Inductive Text Classification. 7. Transductive Text Classification. Part Algorithms. 8. Training Inductive Support Vector Machines. 9. Training Transductive Support Vector Machines. 10. Conclusions. Bibliography. Appendices. Index.
Citation impact
936
total citations
- FWCI
- 10.10
- Percentile
- 100%
- References
- 0
Citations per year
Authors
1Topics & keywords
Keywords
- Support vector machine
- Artificial intelligence
- Notation
- Machine learning
- Computer science
- Relevance vector machine
- Statistical learning theory
- Structured support vector machine
UN Sustainable Development Goals
- Quality Education
No related works found for this paper.