Classification Methods for Internet Applications (Hardcover, 1st ed. 2020)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Big Data, 69
Release date:	2020
First published:	2020
Authors:	Martin Holena • Petr Pulc • Martin Kopp
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	281
Edition:	1st ed. 2020
ISBN-13:	978-3-03-036961-3
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Computing & IT > Applications of computing > Pattern recognition Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Computing & IT > Applications of computing > Databases > Data mining
LSN:	3-03-036961-7
Barcode:	9783030369613

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