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A Churn Analysis Using Data Mining Techniques: Case of Electricity Distribution Company

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61384399%3A31160%2F17%3A00051084" target="_blank" >RIV/61384399:31160/17:00051084 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.iaeng.org/publication/WCECS2017/WCECS2017_pp355-360.pdf" target="_blank" >http://www.iaeng.org/publication/WCECS2017/WCECS2017_pp355-360.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Churn Analysis Using Data Mining Techniques: Case of Electricity Distribution Company

  • Original language description

    Main topics of the document: CRISP-DM; decision tree; churn; data mining; logistic regression

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    50204 - Business and management

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of The World Congress on Engineering and Computer Science 2017

  • ISBN

    978-988-14047-5-6

  • ISSN

    2078-0958

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    355-360

  • Publisher name

    Newswood Limited

  • Place of publication

    San Francisco

  • Event location

    Clark Kerr Campus, UC Berkeley

  • Event date

    Oct 25, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000418106200068