Telecom churn – reproducibility package (code, calibrated scores, models, figures)

This deposit contains code and artifacts for a fully reproducible churn-prediction workflow on IBM’s Telco Customer Churn dataset. The pipeline emphasizes class-imbalance aware model selection (PR-AUC with class weights), probability calibration (isotonic; reported via Brier score and reliability curves), and transparent explainability (global SHAP + local LIME). Calibrated probabilities are mapped to operational risk tiers (Low <0.35, Medium 0.35–0.59, High ≥0.60) to support budgeted retention actions. Contents: (i) training/evaluation scripts, (ii) a calibrated model artifact and evaluation figures (PR/ROC, gains, calibration), (iii) LIME figures and selection logs under a deterministic Plan-A protocol (Top-risk / Median-of-tier / Near-threshold per tier), (iv) audit reports and a Zenodo-ready README. Random seed is fixed to 42 for repeatability. Data availability: we do not redistribute the raw IBM/Kaggle CSV. Users should download WA_Fn-UseC_-Telco-Customer-Churn.csv from the original source and place it in the project root as documented in the README.