Kernels For Structured Data
Download Kernels For Structured Data PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Kernels For Structured Data 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.
Kernels for Structured Data
This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by their atoms and bonds. The book guides the reader from the basics of kernel methods to advanced algorithms and kernel design for structured data. It is thus useful for readers who seek an entry point into the field as well as experienced researchers.
Kernel Methods for Pattern Analysis
Author: John Shawe-Taylor
language: en
Publisher: Cambridge University Press
Release Date: 2004-06-28
Publisher Description