Support Vector Machines Uses


Download Support Vector Machines Uses PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Support Vector Machines Uses book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.

Download

Support Vector Machines: Theory and Applications


Support Vector Machines: Theory and Applications

Author: Lipo Wang

language: en

Publisher: Springer Science & Business Media

Release Date: 2005-06-21


DOWNLOAD





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.

Support Vector Machines Applications


Support Vector Machines Applications

Author: Yunqian Ma

language: en

Publisher: Springer Science & Business Media

Release Date: 2014-02-12


DOWNLOAD





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.

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


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

Author: Nello Cristianini

language: en

Publisher: Cambridge University Press

Release Date: 2000-03-23


DOWNLOAD





This is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software ensure that it forms an ideal starting point for further study. Equally, the book and its associated web site will guide practitioners to updated literature, new applications, and on-line software.