logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

The Nature Of Statistical Learning Theory Vladimir Vapnik

  • SKU: BELL-42998406
The Nature Of Statistical Learning Theory Vladimir Vapnik
$ 31.00 $ 45.00 (-31%)

4.3

8 reviews

The Nature Of Statistical Learning Theory Vladimir Vapnik instant download after payment.

Publisher: Springer Science & Business Media
File Extension: PDF
File size: 10.15 MB
Pages: 314
Author: Vladimir Vapnik
ISBN: 9781475732641, 1475732643
Language: English
Year: 2013

Product desciption

The Nature Of Statistical Learning Theory Vladimir Vapnik by Vladimir Vapnik 9781475732641, 1475732643 instant download after payment.

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.

Related Products