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Twin Support Vector Machines

Models, Extensions and Applications

Jayadeva, Reshma Khemchandani, Suresh Chandra (Autoren)

Buch | Hardcover

XIV, 211 Seiten

2016 | 1st ed. 2017
Springer International Publishing (Verlag)
978-3-319-46184-7 (ISBN)

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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.

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

Erscheinungsdatum	03.11.2016
Reihe/Serie	Studies in Computational Intelligence
Zusatzinfo	XIV, 211 p. 21 illus., 20 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Themenwelt	Technik
Schlagworte	Artificial Intelligence • artificial intelligence (incl. robotics) • Computational Intelligence • Engineering • machine learning • Robotics • Support Vector Machines • Twin Support Vector Machines • TWSVM • Unsupervised and Semi-Supervised Learning
ISBN-10	3-319-46184-2 / 3319461842
ISBN-13	978-3-319-46184-7 / 9783319461847
Zustand	Neuware