Knowledge discovery with support vector machines /
An easy-to-follow introduction to support vector machines. This book provides an in-depth, easy-to-follow introduction to support vector machines drawing only from minimal, carefully motivated technical and mathematical background material. It begins with a cohesive discussion of machine learning an...
| Main Author: | |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Hoboken, N.J. :
Wiley,
©2009.
|
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | An easy-to-follow introduction to support vector machines. This book provides an in-depth, easy-to-follow introduction to support vector machines drawing only from minimal, carefully motivated technical and mathematical background material. It begins with a cohesive discussion of machine learning and goes on to cover:. Knowledge discovery environments;. Describing data mathematically;. Linear decision surfaces and functions;. Perceptron learning;. Maximum margin classifiers;. Support vector machines;. Elements of statistical learning theory;. Multi-class classification;. Regression with supporsupport vector machines;. Novelty detection. Complemented with hands-on exercises, algorithm descriptions, and data sets, Knowledge Discovery with Support Vector Machines is an invaluable textbook for advanced undergraduate and graduate courses. It is also an excellent tutorial on support vector machines for professionals who are pursuing research in machine learning and related areas. |
|---|---|
| Physical Description: | 1 online resource (xv, 246 pages) : illustrations |
| Bibliography: | Includes bibliographical references (pages 231-235) and index. |
| ISBN: | 9780470503041 0470503041 9780470503065 0470503068 |