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Twin support vector machines = model...

Jayadeva.

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Twin support vector machines = models, extensions and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Twin support vector machines/ by Jayadeva, Reshma Khemchandani, Suresh Chandra.
其他題名:	models, extensions and applications /
作者:	Jayadeva.
其他作者:	Khemchandani, Reshma.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	xiv, 211 p. :ill. (some col.), digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Support vector machines. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-46186-1
ISBN:	9783319461861

Twin support vector machines = models, extensions and applications /
Jayadeva.

Twin support vector machinesmodels, extensions and applications /[electronic resource] :by Jayadeva, Reshma Khemchandani, Suresh Chandra. - Cham :Springer International Publishing :2017. - xiv, 211 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.6591860-949X ;. - Studies in computational intelligence ;v.659..

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.

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.

ISBN: 9783319461861

Standard No.: 10.1007/978-3-319-46186-1doiSubjects--Topical Terms:

2058743
Support vector machines.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Twin support vector machines = models, extensions and applications /
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