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
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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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
50204 - Business and management
Result continuities
Project
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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
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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