Asra Inkesar

An Explainable Machine Learning Approach With Density-Regularized Oversampling for Industrial Customer Churn Prediction

A density-regularized SMOTE-ENC framework that specifically incorporates neighbourhood-based density restrictions into the process of creating synthetic samples for mixed-type churn datasets, and selectively retains synthetic minority samples that lie closer to minority class manifolds while being sufficiently distant...