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Studies in Big Data

Classification Methods for Internet Applications

Authors: Holeňa, Martin, Pulc, Petr, Kopp, Martin

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  • Shows that a key functionality of several important Internet applications is actually the functionality of a classifier
  • Describes various statistical and machine learning methods
  • Includes classification methods with potential future use in applications
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  • ISBN 978-3-030-36962-0
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About this book

This book explores internet applications in which a crucial role is played by classification, such as spam filtering, recommender systems, malware detection, intrusion detection and sentiment analysis. It explains how such classification problems can be solved using various statistical and machine learning methods, including K nearest neighbours, Bayesian classifiers, the logit method, discriminant analysis, several kinds of artificial neural networks, support vector machines, classification trees and other kinds of rule-based methods, as well as random forests and other kinds of classifier ensembles. The book covers a wide range of available classification methods and their variants, not only those that have already been used in the considered kinds of applications, but also those that have the potential to be used in them in the future. The book is a valuable resource for post-graduate students and professionals alike.

About the authors

Martin Holeňa is senior researcher at the Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic.

Table of contents (7 chapters)

Table of contents (7 chapters)

Buy this book

eBook $109.00
price for USA in USD (gross)
  • ISBN 978-3-030-36962-0
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $149.99
price for USA in USD
  • ISBN 978-3-030-36961-3
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Classification Methods for Internet Applications
Authors
Series Title
Studies in Big Data
Series Volume
69
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-36962-0
DOI
10.1007/978-3-030-36962-0
Hardcover ISBN
978-3-030-36961-3
Series ISSN
2197-6503
Edition Number
1
Number of Pages
XII, 281
Number of Illustrations
32 b/w illustrations, 29 illustrations in colour
Topics

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