Application of Data Analytics Techniques for Predicting Customer Churn
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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
- Óbudai Egyetem