An Introduction to Support Vector Machines and Other Kernel-based Learning Methods by John Shawe-Taylor, Nello Cristianini

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



Download eBook




An Introduction to Support Vector Machines and Other Kernel-based Learning Methods John Shawe-Taylor, Nello Cristianini ebook
Page: 189
Publisher: Cambridge University Press
ISBN: 0521780195, 9780521780193
Format: chm


Summary: Multivariate kernel-based pattern classification using support vector machines (SVM) with a novel modification to obtain more balanced sensitivity and specificity on unbalanced data-sets (i.e. I will set up and Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). Many SPM users have created tools for neuroimaging analyses that are based on SPM . K-nearest neighbor; Neural network based approaches for meeting a threshold; Partial based clustering; Hierarchical clustering; Probabilistic based clustering; Gaussian Mixture Modelling (GMM) models. Since their appearance in the early nineties, support vector machines and related kernel-based methods have been successfully applied in diverse fields of application such as bioinformatics, fraud detection, construction of insurance tariffs, direct marketing, and data and text As a consequence, SVMs now play an important role in statistical machine learning and are used not only by statisticians, mathematicians, and computer scientists, but also by engineers and data analysts. "An Introduction to Support Vector Machines and Other Kernel-based Learning Methods". This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. The distinction between Toolboxes . You will find here a list of these tools classified between Toolboxes, Utilities, Batch Systems and Templates. Some applications using learning In the next blog post I will select a couple of methods to detect abnormal traffic. It just struck me as an odd coincidence. Shawe, An Introduction to Support Vector Machines and other Kernel-based Learning Methods, Cambridge University Press, New York, 2000.