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Classification methods for internet ...

Holena, Martin.

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Classification methods for internet applications

Record Type:	Electronic resources : Monograph/item
Title/Author:	Classification methods for internet applications/ by Martin Holena, Petr Pulc, Martin Kopp.
Author:	Holena, Martin.
other author:	Pulc, Petr.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xii, 281 p. :ill., digital ;24 cm.
[NT 15003449]:	Important Internet Applications of Classification -- Basic Concepts Concerning Classification -- Some Frequently Used Classification Methods -- Aiming at Predictive Accuracy -- Aiming at Comprehensibility -- A Team Is Superior to an Individual.
Contained By:	Springer eBooks
Subject:	Information filtering systems. -
Online resource:	https://doi.org/10.1007/978-3-030-36962-0
ISBN:	9783030369620

Classification methods for internet applications
Holena, Martin.

Classification methods for internet applications[electronic resource] /by Martin Holena, Petr Pulc, Martin Kopp. - Cham :Springer International Publishing :2020. - xii, 281 p. :ill., digital ;24 cm. - Studies in big data,v.692197-6503 ;. - Studies in big data ;v.69..

Important Internet Applications of Classification -- Basic Concepts Concerning Classification -- Some Frequently Used Classification Methods -- Aiming at Predictive Accuracy -- Aiming at Comprehensibility -- A Team Is Superior to an Individual.

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.

ISBN: 9783030369620

Standard No.: 10.1007/978-3-030-36962-0doiSubjects--Topical Terms:

3447496
Information filtering systems.

LC Class. No.: QA76.9.I58 / H654 2020

Dewey Class. No.: 005.56

Classification methods for internet applications
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100 1 $a Holena, Martin. $3 3447492
245 1 0 $a Classification methods for internet applications $h [electronic resource] / $c by Martin Holena, Petr Pulc, Martin Kopp.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xii, 281 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in big data, $x 2197-6503 ; $v v.69
505 0 $a Important Internet Applications of Classification -- Basic Concepts Concerning Classification -- Some Frequently Used Classification Methods -- Aiming at Predictive Accuracy -- Aiming at Comprehensibility -- A Team Is Superior to an Individual.
520 $a 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.
650 0 $a Information filtering systems. $3 3447496
650 0 $a Classification rule mining. $3 2209888
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Probability and Statistics in Computer Science. $3 891072
650 2 4 $a Pattern Recognition. $3 891045
700 1 $a Pulc, Petr. $3 3447493
700 1 $a Kopp, Martin. $3 3447494
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830 0 $a Studies in big data ; $v v.69. $3 3447495
856 4 0 $u https://doi.org/10.1007/978-3-030-36962-0
950 $a Intelligent Technologies and Robotics (Springer-42732)