Kernel Methods for Pattern Analysis

Kernel Methods for Pattern Analysis

by John Shawe-Taylor, Nello Cristianini
     
 

View All Available Formats & Editions

A unique account of developing topic in data mining and machine learning.See more details below

Overview

A unique account of developing topic in data mining and machine learning.

Editorial Reviews

From the Publisher
"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 especially 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 its 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 also extremely useful."
IAPR Newsletter

"If you are interested in an introduction to statistical techniques for analyzing text documents, Kernel Methods will serve you well."
M. Last, Journal of the American Statistical Association

Product Details

ISBN-13:
9781139636940
Publisher:
Cambridge University Press
Publication date:
12/05/2012
Sold by:
Barnes & Noble
Format:
NOOK Book
File size:
45 MB
Note:
This product may take a few minutes to download.

What People are saying about this

From the Publisher
"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 especially 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 its 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 also extremely useful."
IAPR Newsletter

"If you are interested in an introduction to statistical techniques for analyzing text documents, Kernel Methods will serve you well."
M. Last, Journal of the American Statistical Association

Customer Reviews

Average Review:

Write a Review

and post it to your social network

     

Most Helpful Customer Reviews

See all customer reviews >