Kernel Methods for Pattern Analysis
Zoomicon-zoom-in
Kernel Methods for Pattern Analysis

Kernel Methods for Pattern Analysis

By
John Shawe-Taylor (Author) Nello Cristianini (Author)  

Hardback

Available / dispatched within 1 - 2 weeks

Quantity
Kernel methods provide a powerful and unified framework for pattern discovery, motivating algorithms that can act on general types of data (e.g. strings, vectors or text) and look for general types of relations (e.g. rankings, classifications, regressions, clusters). The application areas range from neural networks and pattern recognition to machine learning and data mining. This book, developed from lectures and tutorials, fulfils two major roles: firstly it provides practitioners with a large toolkit of algorithms, kernels and solutions ready to use for standard pattern discovery problems in fields such as bioinformatics, text analysis, image analysis. Secondly it provides an easy introduction for students and researchers to the growing field of kernel-based pattern analysis, demonstrating with examples how to handcraft an algorithm or a kernel for a new specific application, and covering all the necessary conceptual and mathematical tools to do so. 6 Tables, unspecified
fm.author_biographical_note1 fm.author_biographical_note2
  • Contributor: John Shawe-Taylor
  • Imprint: Cambridge University Press
  • ISBN13: 9780521813976
  • Number of Pages: 478
  • Packaged Dimensions: 170x249x30mm
  • Packaged Weight: 1000
  • Format: Hardback
  • Publisher: Cambridge University Press
  • Release Date: 2004-06-28
  • Binding: Hardback
  • Biography: fm.author_biographical_note1 fm.author_biographical_note2

Delivery Options

Home Delivery

Store Delivery

Free Returns

We hope you are delighted with everything you buy from us. However, if you are not, we will refund or replace your order up to 30 days after purchase. Terms and exclusions apply; find out more from our Returns and Refunds Policy.