Twin Support Vector Machines
Models, Extensions and Applications
Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing
| Author: | Jayadeva, Reshma Khemchandani, Suresh Chandra | ISBN: | 9783319461861 |
| Publisher: | Springer International Publishing | Publication: | October 12, 2016 |
| Imprint: | Springer | Language: | English |
| Author: | Jayadeva, Reshma Khemchandani, Suresh Chandra |
| ISBN: | 9783319461861 |
| Publisher: | Springer International Publishing |
| Publication: | October 12, 2016 |
| Imprint: | Springer |
| Language: | English |
This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most of the basic models of TWSVM and twin support vector regression (TWSVR) available in the literature, it also discusses the important and challenging applications of this new machine learning methodology. A chapter on “Additional Topics” has been included to discuss kernel optimization and support tensor machine topics, which are comparatively new but have great potential in applications. It is primarily written for graduate students and researchers in the area of machine learning and related topics in computer science, mathematics, electrical engineering, management science and finance.
This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most of the basic models of TWSVM and twin support vector regression (TWSVR) available in the literature, it also discusses the important and challenging applications of this new machine learning methodology. A chapter on “Additional Topics” has been included to discuss kernel optimization and support tensor machine topics, which are comparatively new but have great potential in applications. It is primarily written for graduate students and researchers in the area of machine learning and related topics in computer science, mathematics, electrical engineering, management science and finance.
