Martin Holeňa & Petr Pulc 
Classification Methods for Internet Applications [PDF ebook] 

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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.

€96.29
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Table des matières

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.

A propos de l’auteur

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

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Langue Anglais ● Format PDF ● Pages 281 ● ISBN 9783030369620 ● Taille du fichier 6.3 MB ● Maison d’édition Springer International Publishing ● Lieu Cham ● Pays CH ● Publié 2020 ● Téléchargeable 24 mois ● Devise EUR ● ID 7372064 ● Protection contre la copie DRM sociale

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