You might also like

More about Learning to Classify Text Using Support Vector Machines

• Book details
• Synopsis
• Trending among others

You get 249 loyalty points

Book synopsis

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.

Book details

Book category Books in English Computing & information technology Computer science Artificial intelligence

• Full title: Learning to Classify Text Using Support Vector Machines
• Subtitle: Methods, Theory and Algorithms
• Author: Thorsten Joachims
• Language: English
• Binding: Hardback
• Number of pages: 205
• EAN: 9780792376798
• ISBN: 079237679X
• ID: 01397195
• Publisher: Springer
• Weight: 1100 g
• Dimensions: 235 × 155 × 17 mm
• Date of publishing: 15. April 2002

Trending among others

---

---

---