Twin Support Vector Machines
Models, Extensions and Applications
Published on 12. October 2016
XIV, 211 pages
978-3-319-46186-1 (ISBN)
Description
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.
More details
Series
Edition
1st ed. 2017
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XIV, 211 p. 21 illus., 20 illus. in color.
File size
4,10 MB
ISBN-13
978-3-319-46186-1 (9783319461861)
DOI
10.1007/978-3-319-46186-1
Schweitzer Classification
Other editions
Additional editions
Jayadeva | Reshma Khemchandani | Suresh Chandra
Twin Support Vector Machines
Models, Extensions and Applications
Book
10/2016
Springer
€106.99
Shipment within 10-15 days
Persons
Content
Introduction.- Generalized Eigenvalue Proximal Support Vector Machines.- Twin Support Vector Machines (TWSVM) for Classification.- TWSVR: Twin Support Vector Machine Based Regression.- Variants of Twin Support Vector Machines: Some More Formulations.- TWSVM for Unsupervised and Semi-Supervised Learning.- Some Additional Topics.- Applications Based on TWSVM.- References
