Support Vector Machines and Perceptrons, Murty

Автор: Shigeo Abe
Название: Support Vector Machines for Pattern Classification
ISBN: 1447125487 ISBN-13(EAN): 9781447125488
Издательство: Springer
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Цена: 22201.00 р.
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Описание: This guide on the use of SVMs in pattern classification includes a rigorous performance comparison of classifiers and regressors. The book takes the unique approach of focusing on classification rather than covering the theoretical aspects of SVMs.

Автор: Jayadeva; Reshma Khemchandani; Suresh Chandra
Название: Twin Support Vector Machines
ISBN: 3319461842 ISBN-13(EAN): 9783319461847
Издательство: Springer
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Цена: 19564.00 р.
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Описание: 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.

Автор: Ingo Steinwart; Andreas Christmann
Название: Support Vector Machines
ISBN: 1489989633 ISBN-13(EAN): 9781489989635
Издательство: Springer
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Цена: 20962.00 р.
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Описание: In a nutshell, we identify at least three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness against several types of model violations and outliers, and last but not least their computational e?ciency compared with several other methods.