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Application of Data Analytics Techniques for Predicting Customer Churn

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URI
http://hdl.handle.net/20.500.14044/31941
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  • Acta Polytechnica Hungarica [175]
Abstract
This paper deals with the classification of bank customers based on their characteristics. The aim of this research is to provide an optimal model capable of identifying customers who plan to leave the bank in the near future and switch to competitors. Identifying the customers is crucial because it allows you to allocate funds to marketing more efficiently and ensure competitiveness. As part of the paper, the data were first adequately pre-processed, which was followed by the compilation of eight classification models. These models were then divided into two groups according to the approach to solving class imbalances in the target attribute.
Title
Application of Data Analytics Techniques for Predicting Customer Churn
Author
Biceková, Anna
Lohaj, Oliver
Babič, František
Puškáš, Marek
xmlui.dri2xhtml.METS-1.0.item-date-issued
2025
xmlui.dri2xhtml.METS-1.0.item-rights-access
Open access
xmlui.dri2xhtml.METS-1.0.item-identifier-issn
1785-8860
xmlui.dri2xhtml.METS-1.0.item-language
en
xmlui.dri2xhtml.METS-1.0.item-format-page
16 p.
xmlui.dri2xhtml.METS-1.0.item-subject-oszkar
customer churn, classification, class imbalance, competitiveness
xmlui.dri2xhtml.METS-1.0.item-description-version
Kiadói változat
xmlui.dri2xhtml.METS-1.0.item-identifiers
DOI: 10.12700/APH.22.7.2025.7.5
xmlui.dri2xhtml.METS-1.0.item-other-containerTitle
Acta Polytechnica Hungarica
xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalYear
2025
xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalVolume
22. évf.
xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalNumber
7. sz.
xmlui.dri2xhtml.METS-1.0.item-type-type
Tudományos cikk
xmlui.dri2xhtml.METS-1.0.item-subject-area
Műszaki tudományok - informatikai tudományok
xmlui.dri2xhtml.METS-1.0.item-publisher-university
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