Classification Methods for Internet Applications

Martin Holeňa, Petr Pulc, Martin Kopp

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English

Springer Nature Switzerland AG
30 January 2021

Probability & statistics; Data mining; Maths for computer scientists; Artificial intelligence; Expert & knowledge-based systems

Series: Studies in Big Data

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.

By: Martin Holeňa, Petr Pulc, Martin Kopp
Imprint: Springer Nature Switzerland AG
Country of Publication: Switzerland
Edition: 1st ed. 2020
Volume: 69
Dimensions: Height: 235mm, Width: 155mm,
Weight: 456g
ISBN: 9783030369644
ISBN 10: 3030369641
Series: Studies in Big Data
Pages: 281
Publication Date: 30 January 2021
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

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