Twin support vector machines : models, extensions and applications

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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. -- Nakladatelská anotace … full description

Bibliographic Details

Main Author

Jayadeva

Other Authors

Reshma Khemchandani
Suresh Chandra
SpringerLink (online služba)

Document Type

Books

Physical Description

1 online zdroj (xiv, 211 stran) : barevné ilustrace

Published

Cham, Switzerland : Springer, [2017]

Series

Studies in computational intelligence

Subjects

umělá inteligence > vt

učící se systémy > vt

strojové učení

výpočetní inteligence

computational intelligence

kolektivní monografie

elektronické knihy

Bibliography

Obsahuje bibliografii, bibliografické odkazy a rejstřík

ISBN

978-3-319-46186-1

Contents

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