May 11, 2005 · This is a book about learning from empirical data (i.e., examples, samples, measurements, records, patterns or observations) by applying support vector machines …

Support Vector Machine (SVM) Support vectors Maximize margin •SVMs maximize the margin (Winston terminology: the ‘street’) around the separating hyperplane. •The decision function is …

“A mathematically elaborated topic of support vector machines in a book full with definitions and lemmas. It presents support vector machines (SVMs) as a successful modeling and prediction …

Book description This is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances in statistical learning theory.

Support Vector Machines (SVM’s) are a relatively new learning method used for binary classi cation. The basic idea is to nd a hyperplane which separates the d-dimensional data perfectly …

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, …

Jun 21, 2005 · 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 …

Jan 31, 2015 · There is a book named $\textbf{An Introduction to Support Vector Machines and Other Kernel-based Learning Methods}$ and is dedicated entirely to SVM covering both …

Apr 1, 2009 · information retrieval problems, particularly text classification. An SVM is a kind of large-margin classifier: it is a vector space based machine learning method where the goal is …