Classification Methods for Internet Applications (Studies in Big Data) - Softcover

Holeňa, Martin; Pulc, Petr; Kopp, Martin

Softcover

ISBN 10: 3030369641 ISBN 13: 9783030369644

Publisher: Springer, 2021

Synopsis

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 this title

About the Author

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

From the Back Cover

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.

Edition details

• Publisher: Springer
• Publication date: 2021
• Language: English
• ISBN 10: 3030369641
• ISBN 13: 9783030369644
• Binding: Paperback
• Edition number: 1
• Number of pages: 296