- Paperback: 514 pages
- Publisher: Wiley-Blackwell; 2nd Edition edition (18 July 2002)
- Language English
- ISBN-10: 0470845147
- ISBN-13: 978-0470845141
- Product Dimensions: 24 x 16.8 x 2.8 cm
- Amazon Bestsellers Rank: 1,176,946 in Books (See Top 100 in Books)
- See Complete Table of Contents
| ||||||||||||||||||
Did you know you can trade in your old books for an Amazon.co.uk Gift Card to spend on the things you want? Plus, get an extra £5 Gift Certificate when you trade in books worth £10 or more before June 30, 2012. Visit the Books Trade-In Store for more details. |
Product details |
More About the Author
Product Description
Review
... features a "how to" approach with examples and exercises,Lavoiser,
--This text refers to an out of print or unavailable edition of this title.
Review
"...an excellent self--contained introductory text..." (Technometrics, Vol. 45, No. 4, November 2003)
--This text refers to an out of print or unavailable edition of this title.
Inside This Book
(Learn More)
First Sentence
This book describes basic pattern recognition procedures, together with practical applications of the techniques on real-world problems. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
This book describes basic pattern recognition procedures, together with practical applications of the techniques on real-world problems. Read the first page
Explore More
Concordance
Browse Sample PagesConcordance
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Tags Customers Associate with This Product(What's this?)Click on a tag to find related items, discussions, and people.
|
Sell a Digital Version of This Book in the Kindle Store
If you are a publisher or author and hold the digital rights to a book, you can sell a digital version of it in our Kindle Store.
Learn more
Customer Reviews
There are no customer reviews yet on Amazon.co.uk.
5 star
4 star
3 star
2 star
1 star
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
3 reviews
3 of 3 people found the following review helpful
The most comprehensive book about machine learning
21 Feb 2008
Format:Paperback|Amazon Verified Purchase
The book written by Andrew Webb is certainly the most comprehensive book related to machine learning. I have not been able to find any machine learning topic which is not treated in this book.
According to me, this book is more for a scientific audience for the simplest reason that the presentation gives more importance to equations than to application examples. It does not explain how to program machine learning algorithm but rather which algorithms exist and what is their mathematical background. Every technique is presented first using text and only then mathematical development is shown. Therefore, it is convenient for people preferring textual description as well as the ones preferring equations.
The book is very well structured. Every chapter starts with a textual introduction on the related issue and then describes several techniques to solve it. At the end, specific application examples are given. A large part is then devoted to summary, discussion, recommendations (not always), notes and references, and finally exercises. Topics are covered in a non standard way for people used to data mining practical books. After an introduction, density estimation techniques are explained. Then linear and non-linear discriminant analyzes. It goes on with decision trees, performance and feature selection to finish with clustering and some other additional topics. Although this book is written in a statistical point of view, it is certainly one of the most comprehensive resource for machine learning and data mining.
According to me, this book is more for a scientific audience for the simplest reason that the presentation gives more importance to equations than to application examples. It does not explain how to program machine learning algorithm but rather which algorithms exist and what is their mathematical background. Every technique is presented first using text and only then mathematical development is shown. Therefore, it is convenient for people preferring textual description as well as the ones preferring equations.
The book is very well structured. Every chapter starts with a textual introduction on the related issue and then describes several techniques to solve it. At the end, specific application examples are given. A large part is then devoted to summary, discussion, recommendations (not always), notes and references, and finally exercises. Topics are covered in a non standard way for people used to data mining practical books. After an introduction, density estimation techniques are explained. Then linear and non-linear discriminant analyzes. It goes on with decision trees, performance and feature selection to finish with clustering and some other additional topics. Although this book is written in a statistical point of view, it is certainly one of the most comprehensive resource for machine learning and data mining.
7 of 20 people found the following review helpful
Very Bad treatment of the subject
12 Jan 2006
Format:Paperback
The author claims that this book is written for senior undergrads and gaduate students, on the contraray, of what he claimed, his treatment of the suject is very sketchy. He has written this book in a somewhat citational manner i.e not treating any details of the concerned topics whatsoever and only stating the facts directly like he is citing some kind of terminolgy and not intersted in giving the reader a thourough understanding of the subject.
He has given extensive references and urls and so this book is more like " I can't explain anything go search urself here".
I think its the most worst way anybody could adopt for writing a book. In my opinion the only purpose of this book was to have a publication on his credit.
I would strongly recommend any students to refrain from buying this one as it will not help you much in any way.
Or else if u realy like to use very expensive toilet paper then give this book a try.
He has given extensive references and urls and so this book is more like " I can't explain anything go search urself here".
I think its the most worst way anybody could adopt for writing a book. In my opinion the only purpose of this book was to have a publication on his credit.
I would strongly recommend any students to refrain from buying this one as it will not help you much in any way.
Or else if u realy like to use very expensive toilet paper then give this book a try.
7 of 28 people found the following review helpful
This book is good guidance.
3 Nov 2000
Format:Paperback
I recently started study about Pattern Recognition. This book is so well organized.
- Introduction to statistical pattern recognition
- Basic approaches to supervised classification via Bayes' rule and estimation of the class-conditional densities.
- Discriminant function approach to supervised classification.
- Techniques of exploratory data analysis.
- Additional topics on pattern recognition including performance assessment.
Especially, this book contains URL which concerned with topics. It is very useful!!
Were these reviews helpful?
Let us know
Listmania!
Look for similar items by category
- Books > Computing & Internet > Digital Lifestyle > Online Shopping > Amazon
- Books > Computing & Internet > Software & Graphics
- Books > Science & Nature > Mathematics > Applied Mathematics
- Books > Science & Nature > Mathematics > Probability & Statistics
- Books > Science & Nature > Popular Science > Maths
- Books > Scientific, Technical & Medical
Look for similar items by subject
Feedback
- Would you like to update product info or give feedback on images?
- I am the Author, and I want to comment on my book.
- I am the Publisher, and I want to comment on this book.
