Kernel Methods for Pattern Analysis (inbunden)
Inbunden (Hardback)
Antal sidor
illustrated ed
Cambridge University Press
Cristianini, Nello
33 figures 6 tables
255 x 180 x 25 mm
1134 g
Antal komponenter
69:B&W 6.69 x 9.61 in or 244 x 170 mm (Pinched Crown) Case Laminate on White w/Gloss Lam
Kernel Methods for Pattern Analysis (inbunden)

Kernel Methods for Pattern Analysis

Inbunden Engelska, 2004-06-01
Skickas inom 10-15 vardagar.
Fri frakt inom Sverige för privatpersoner.
Finns även som
Visa alla 2 format & utgåvor
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.
Visa hela texten

Passar bra ihop

  1. Kernel Methods for Pattern Analysis
  2. +
  3. Learning Theory

De som köpt den här boken har ofta också köpt Learning Theory av John Shawe-Taylor, Yoram Singer (häftad).

Köp båda 2 för 2178 kr


Har du läst boken? Sätt ditt betyg »

Recensioner i media

'Kernel methods form an important aspect of modern pattern analysis, and this book gives a lively and timely account of such methods. ... if you want to get a good idea of the current research in this field, this book cannot be ignored.' SIAM Review

'... the book provides an excellent overview of this growing field. I highly recommend it to those who are interested in pattern analysis and machine learning, and especailly to those who want to apply kernel-based methods to text analysis and bioinformatics problems.' Computing Reviews

' ... I enjoyed reading this book and am happy about is addition to my library as it is a valuable practitioner's reference. I especially liked the presentation of kernel-based pattern analysis algorithms in terse mathematical steps clearly identifying input data, output data, and steps of the process. The accompanying Matlab code or pseudocode is al extremely useful.' IAPR Newsletter

Bloggat om Kernel Methods for Pattern Analysis

Övrig information

fm.author_biographical_note1 fm.author_biographical_note2


Preface; Part I. Basic Concepts: 1. Pattern analysis; 2. Kernel methods: an overview; 3. Properties of kernels; 4. Detecting stable patterns; Part II. Pattern Analysis Algorithms: 5. Elementary algorithms in feature space; 6. Pattern analysis using eigen-decompositions; 7. Pattern analysis using convex optimisation; 8. Ranking, clustering and data visualisation; Part III. Constructing Kernels: 9. Basic kernels and kernel types; 10. Kernels for text; 11. Kernels for structured data: strings, trees, etc.; 12. Kernels from generative models; Appendix A: proofs omitted from the main text; Appendix B: notational conventions; Appendix C: list of pattern analysis methods; Appendix D: list of kernels; References; Index.