Počet záznamů: 1  

Classification Methods for Internet Applications

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    SYSNO ASEP0522793
    Druh ASEPB - Monografie
    Zařazení RIVB - Odborná monografie, kniha
    NázevClassification Methods for Internet Applications
    Tvůrce(i) Holeňa, Martin (UIVT-O) SAI, RID
    Pulc, P. (CZ)
    Kopp, M. (CZ)
    Vyd. údajeSpringer: Cham, 2020
    ISBN978-3-030-36961-3
    EdiceStudies in Big Data
    Č. sv. edice69
    Poč.str.281 s.
    Forma vydáníTištěná - P
    Jazyk dok.eng - angličtina
    Země vyd.CH - Švýcarsko
    Klíč. slovaSpam filtering ; Recommender systems ; Malware detection ; Network intrusion detection ; Random forests ; Classifier comprehensibility ; Support vector machines ; Nearest neighbours classification ; Bayesian classifiers
    Vědní obor RIVIN - Informatika
    Obor OECDComputer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Institucionální podporaUIVT-O - RVO:67985807
    DOI10.1007/978-3-030-36962-0
    AnotaceThis 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.
    PracovištěÚstav informatiky
    KontaktTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Rok sběru2021
Počet záznamů: 1