Applying CHAID for logistic regression diagnostics and classification accuracy improvement [PDF]
In this study a CHAID-based approach to detecting classification accuracy heterogeneity across segments of observations is proposed. This helps to solve some important problems, facing a model-builder: 1. How to automatically detect segments in which the
Antipov, Evgeny, Pokryshevskaya, Elena
core
Machine Learning–Based Customer Churn Prediction in Telecommunication Industry
Applied Computational Intelligence and Soft ComputingCustomer churn remains a major challenge in the telecommunications industry, where retaining existing customers is significantly more cost-effective than acquiring new ones.
Henry Nii-Armah Mettle +2 more
doaj +1 more source
The customer churn process is vital to a company’s profitability, which indicates that the company needs to adapt to evolving customer demand and adopt disruptive technologies such as generative artificial intelligence (AI) to remain competitive.
Hoff, Fredrik
core +3 more sources
Subscriber churn in the Australian ISP market [PDF]
Rapid growth in Internet use, combined with easy market entry by Internet service providers (ISPs), has resulted in a highly competitive supply of Internet services.
Savage, Scott J +2 more
core
A hybrid feature selection framework for dimensionality-optimized customer churn prediction. [PDF]
Sci RepOmar AS, Ogada K, Tole K.
europepmc +1 more source
Customer churn prediction in privacy-preserving HashCode-based security abstractions. [PDF]
Sci RepMunshi A.
europepmc +1 more source
A novel hybrid deep learning framework for customer churn prediction using RFM and embedding clustering. [PDF]
Sci RepIbrahim S +3 more
europepmc +1 more source
Calibrated, cost-sensitive, explainable ensemble learning for customer churn prediction in retail banking: a leakage-safe pipeline and single-dataset case study. [PDF]
Front Artif IntellKarim F +7 more
europepmc +1 more source
Improving bank customer churn prediction with feature reduction using GA. [PDF]
Sci RepT N N, Pramod D.
europepmc +1 more source
Explainable AI-driven customer churn prediction: a multi-model ensemble approach with SHAP-based feature analysis. [PDF]
Front Artif IntellEl Attar A, El-Hajj M.
europepmc +1 more source