Classification Methods for Internet Applications

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F20%3A00522793" target="_blank" >RIV/67985807:_____/20:00522793 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21240/20:00339837

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-030-36962-0" target="_blank" >http://dx.doi.org/10.1007/978-3-030-36962-0</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-36962-0" target="_blank" >10.1007/978-3-030-36962-0</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Classification Methods for Internet Applications

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Classification Methods for Internet Applications

Popis výsledku anglicky

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.

Druh

B - Odborná kniha

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA18-18080S" target="_blank" >GA18-18080S: Objevování znalostí v datech o aktivitě člověka založené na fúzi</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

ISBN

978-3-030-36961-3

Počet stran knihy

281

Název nakladatele

Cham

Místo vydání

Springer

Kód UT WoS knihy

—