Classification Methods for Internet Applications - Martin Kopp,Petr Pulc,Martin Hole¿a
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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 ... Pilns apraksts
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Aprašymas
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.
Vairāk informācijas
| Autors | Martin Kopp, Petr Pulc, Martin Hole¿a |
|---|---|
| Izdevējs | Springer Nature Switzerland |
| Izlaides gads | 2020 |
| Vāka tips | Cietais vāks |
| EAN | 9783030369613 |