Jayadeva.
Twin Support Vector Machines Models, Extensions and Applications / [electronic resource] : - 1st ed. 2017. - XIV, 211 p. 21 illus., 20 illus. in color. | Binding - Card Paper | - Studies in Computational Intelligence, 659 1860-949X ; . - Studies in Computational Intelligence, 659 .
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.
9783319461861
Mechanical Engineering
Computational Intelligence. Artificial Intelligence.
006.3
Twin Support Vector Machines Models, Extensions and Applications / [electronic resource] : - 1st ed. 2017. - XIV, 211 p. 21 illus., 20 illus. in color. | Binding - Card Paper | - Studies in Computational Intelligence, 659 1860-949X ; . - Studies in Computational Intelligence, 659 .
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.
9783319461861
Mechanical Engineering
Computational Intelligence. Artificial Intelligence.
006.3