Towards Explainable Machine Learning for Bank Churn Prediction Using Data Balancing and Ensemble-Based Methods

Towards Explainable Machine Learning for Bank Churn Prediction Using Data Balancing and Ensemble-Based Methods

The diversity of data collected on both social networks and digital interfaces is extremely increased, raising the problem of heterogeneous variables that are not often favourable to classification algorithms. Despite the significant improvement in machine learning (ML) and predictive analysis effic...

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Bibliographic Details
Main Authors: Stéphane C. K. Tékouabou, Ștefan Cristian Gherghina, Hamza Toulni, Pedro Neves Mata, José Moleiro Martins
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Mathematics
Subjects:
SMOTE
heterogeneous data
imbalance data
machine learning
shapley values
ensemble methods
Online Access:https://www.mdpi.com/2227-7390/10/14/2379

Internet

https://www.mdpi.com/2227-7390/10/14/2379

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