Learning with Support Vector Machines, Colin Campbell, Ying Yiming

Автор: Ingo Steinwart; Andreas Christmann
Название: Support Vector Machines
ISBN: 1489989633 ISBN-13(EAN): 9781489989635
Издательство: Springer
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Цена: 139750.00 T
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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.

Автор: Jayadeva; Reshma Khemchandani; Suresh Chandra
Название: Twin Support Vector Machines
ISBN: 3319461842 ISBN-13(EAN): 9783319461847
Издательство: Springer
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Цена: 130430.00 T
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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: Catalin Stoean; Ruxandra Stoean
Название: Support Vector Machines and Evolutionary Algorithms for Classification
ISBN: 3319069403 ISBN-13(EAN): 9783319069401
Издательство: Springer
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Цена: 121890.00 T
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Описание: When discussing classification, support vector machines are known to be a capable and efficient technique to learn and predict with high accuracy within a quick time frame.

Автор: Catalin Stoean; Ruxandra Stoean
Название: Support Vector Machines and Evolutionary Algorithms for Classification
ISBN: 3319382438 ISBN-13(EAN): 9783319382432
Издательство: Springer
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Цена: 104480.00 T
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Описание: When discussing classification, support vector machines are known to be a capable and efficient technique to learn and predict with high accuracy within a quick time frame.

Автор: Joachim Diederich
Название: Rule Extraction from Support Vector Machines
ISBN: 3642094635 ISBN-13(EAN): 9783642094637
Издательство: Springer
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Цена: 130590.00 T
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Описание: Support vector machines (SVMs) are one of the most active research areas in machine learning. For SVMs to gain a wider degree of acceptance in fields such as medical diagnosis and security sensitive areas, it is desirable to offer an explanation capability.

Автор: Mario Neto Borges; Nival Nunes de Almeida
Название: Intelligent Educational Machines
ISBN: 3642079539 ISBN-13(EAN): 9783642079535
Издательство: Springer
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Цена: 158380.00 T
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Описание: This book presents recent advances in intelligent educational machines. It will be of particular interest to engineers, researchers, and graduate students in Computational Intelligence.

Автор: Kelly John E., Hamm Steve
Название: Smart Machines: IBM`s Watson and the Era of Cognitive Computing
ISBN: 023116856X ISBN-13(EAN): 9780231168564
Издательство: Wiley
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Цена: 20050.00 T
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Описание:

We are crossing a new frontier in the evolution of computing and entering the era of cognitive systems. The victory of IBM's Watson on the television quiz show Jeopardy revealed how scientists and engineers at IBM and elsewhere are pushing the boundaries of science and technology to create machines that sense, learn, reason, and interact with people in new ways to provide insight and advice.

In Smart Machines, John E. Kelly III, director of IBM Research, and Steve Hamm, a writer at IBM and a former business and technology journalist, introduce the fascinating world of "cognitive systems" to general audiences and provide a window into the future of computing. Cognitive systems promise to penetrate complexity and assist people and organizations in better decision making. They can help doctors evaluate and treat patients, augment the ways we see, anticipate major weather events, and contribute to smarter urban planning. Kelly and Hamm's comprehensive perspective describes this technology inside and out and explains how it will help us conquer the harnessing and understanding of "big data," one of the major computing challenges facing businesses and governments in the coming decades. Absorbing and impassioned, their book will inspire governments, academics, and the global tech industry to work together to power this exciting wave in innovation.