Support Vector Machines: Theory and Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540243885
Total Pages : 456 pages
Book Rating : 4.87/5 ( download)

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Book Synopsis Support Vector Machines: Theory and Applications by : Lipo Wang

Download or read book Support Vector Machines: Theory and Applications written by Lipo Wang and published by Springer Science & Business Media. This book was released on 2005-06-21 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: The support vector machine (SVM) has become one of the standard tools for machine learning and data mining. This carefully edited volume presents the state of the art of the mathematical foundation of SVM in statistical learning theory, as well as novel algorithms and applications. Support Vector Machines provides a selection of numerous real-world applications, such as bioinformatics, text categorization, pattern recognition, and object detection, written by leading experts in their respective fields.

Machine Learning and Its Applications

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Publisher : Springer
ISBN 13 : 3540446737
Total Pages : 334 pages
Book Rating : 4.36/5 ( download)

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Book Synopsis Machine Learning and Its Applications by : Georgios Paliouras

Download or read book Machine Learning and Its Applications written by Georgios Paliouras and published by Springer. This book was released on 2003-06-29 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years machine learning has made its way from artificial intelligence into areas of administration, commerce, and industry. Data mining is perhaps the most widely known demonstration of this migration, complemented by less publicized applications of machine learning like adaptive systems in industry, financial prediction, medical diagnosis and the construction of user profiles for Web browsers. This book presents the capabilities of machine learning methods and ideas on how these methods could be used to solve real-world problems. The first ten chapters assess the current state of the art of machine learning, from symbolic concept learning and conceptual clustering to case-based reasoning, neural networks, and genetic algorithms. The second part introduces the reader to innovative applications of ML techniques in fields such as data mining, knowledge discovery, human language technology, user modeling, data analysis, discovery science, agent technology, finance, etc.

Support Vector Machines

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Publisher : Springer Science & Business Media
ISBN 13 : 0387772421
Total Pages : 611 pages
Book Rating : 4.24/5 ( download)

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Book Synopsis Support Vector Machines by : Ingo Steinwart

Download or read book Support Vector Machines written by Ingo Steinwart and published by Springer Science & Business Media. This book was released on 2008-09-15 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical. David Hilbert The goal of this book is to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni?ed style. 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. Although there are several roots and precursors of SVMs, these methods gained particular momentum during the last 15 years since Vapnik (1995, 1998) published his well-known textbooks on statistical learning theory with aspecialemphasisonsupportvectormachines. Sincethen,the?eldofmachine learninghaswitnessedintenseactivityinthestudyofSVMs,whichhasspread moreandmoretootherdisciplinessuchasstatisticsandmathematics. Thusit seems fair to say that several communities are currently working on support vector machines and on related kernel-based methods. Although there are many interactions between these communities, we think that there is still roomforadditionalfruitfulinteractionandwouldbegladifthistextbookwere found helpful in stimulating further research. Many of the results presented in this book have previously been scattered in the journal literature or are still under review. As a consequence, these results have been accessible only to a relativelysmallnumberofspecialists,sometimesprobablyonlytopeoplefrom one community but not the others.

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

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Publisher : Cambridge University Press
ISBN 13 : 9780521780193
Total Pages : 216 pages
Book Rating : 4.95/5 ( download)

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Book Synopsis An Introduction to Support Vector Machines and Other Kernel-based Learning Methods by : Nello Cristianini

Download or read book An Introduction to Support Vector Machines and Other Kernel-based Learning Methods written by Nello Cristianini and published by Cambridge University Press. This book was released on 2000-03-23 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a comprehensive introduction to Support Vector Machines, a generation learning system based on advances in statistical learning theory.

Support Vector Machines Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 3319023004
Total Pages : 306 pages
Book Rating : 4.07/5 ( download)

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Book Synopsis Support Vector Machines Applications by : Yunqian Ma

Download or read book Support Vector Machines Applications written by Yunqian Ma and published by Springer Science & Business Media. This book was released on 2014-02-12 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Support vector machines (SVM) have both a solid mathematical background and practical applications. This book focuses on the recent advances and applications of the SVM, such as image processing, medical practice, computer vision, and pattern recognition, machine learning, applied statistics, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications.

Knowledge Discovery with Support Vector Machines

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Publisher : John Wiley & Sons
ISBN 13 : 1118211030
Total Pages : 211 pages
Book Rating : 4.38/5 ( download)

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Book Synopsis Knowledge Discovery with Support Vector Machines by : Lutz H. Hamel

Download or read book Knowledge Discovery with Support Vector Machines written by Lutz H. Hamel and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: An easy-to-follow introduction to support vector machines This book provides an in-depth, easy-to-follow introduction to support vector machines drawing only from minimal, carefully motivated technical and mathematical background material. It begins with a cohesive discussion of machine learning and goes on to cover: Knowledge discovery environments Describing data mathematically Linear decision surfaces and functions Perceptron learning Maximum margin classifiers Support vector machines Elements of statistical learning theory Multi-class classification Regression with support vector machines Novelty detection Complemented with hands-on exercises, algorithm descriptions, and data sets, Knowledge Discovery with Support Vector Machines is an invaluable textbook for advanced undergraduate and graduate courses. It is also an excellent tutorial on support vector machines for professionals who are pursuing research in machine learning and related areas.

Support Vector Machines

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Publisher : CRC Press
ISBN 13 : 1439857938
Total Pages : 345 pages
Book Rating : 4.39/5 ( download)

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Book Synopsis Support Vector Machines by : Naiyang Deng

Download or read book Support Vector Machines written by Naiyang Deng and published by CRC Press. This book was released on 2012-12-17 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)-classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs since optimization is one of the pillars on which

Learning with Kernels

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Publisher : MIT Press
ISBN 13 : 0262536579
Total Pages : 645 pages
Book Rating : 4.78/5 ( download)

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Book Synopsis Learning with Kernels by : Bernhard Scholkopf

Download or read book Learning with Kernels written by Bernhard Scholkopf and published by MIT Press. This book was released on 2018-06-05 with total page 645 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics. Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

A Gentle Introduction to Support Vector Machines in Biomedicine: Theory and methods

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Publisher : World Scientific
ISBN 13 : 9814324388
Total Pages : 200 pages
Book Rating : 4.80/5 ( download)

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Book Synopsis A Gentle Introduction to Support Vector Machines in Biomedicine: Theory and methods by : Alexander Statnikov

Download or read book A Gentle Introduction to Support Vector Machines in Biomedicine: Theory and methods written by Alexander Statnikov and published by World Scientific. This book was released on 2011 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Support Vector Machines (SVMs) are among the most important recent developments in pattern recognition and statistical machine learning. They have found a great range of applications in various fields including biology and medicine. However, biomedical researchers often experience difficulties grasping both the theory and applications of these important methods because of lack of technical background. The purpose of this book is to introduce SVMs and their extensions and allow biomedical researchers to understand and apply them in real-life research in a very easy manner. The book is to consist of two volumes: theory and methods (Volume 1) and cases studies (Volume 2).The proposed book follows the approach of ?programmed learning? whereby material is presented in short sections called ?frames?. Each frame consists of a very small amount of information to be learned, a multiple choice quiz, and answers to the quiz. The reader can proceed to the next frame only after verifying the correct answers to the current frame.

Support Vector Machines and Their Application in Chemistry and Biotechnology

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Publisher : CRC Press
ISBN 13 : 1439821283
Total Pages : 206 pages
Book Rating : 4.82/5 ( download)

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Book Synopsis Support Vector Machines and Their Application in Chemistry and Biotechnology by : Yizeng Liang

Download or read book Support Vector Machines and Their Application in Chemistry and Biotechnology written by Yizeng Liang and published by CRC Press. This book was released on 2016-04-19 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Support vector machines (SVMs) are used in a range of applications, including drug design, food quality control, metabolic fingerprint analysis, and microarray data-based cancer classification. While most mathematicians are well-versed in the distinctive features and empirical performance of SVMs, many chemists and biologists are not as familiar wi