user@devops:~$ cat README.md
Cross-Validation — Churn Prediction
# Description
Cross-validation and advanced metrics project for telecom churn prediction (4,000 customers, ~20% churn). Learn K-Fold Cross Validation for reliable performance estimation, Stratified K-Fold for maintaining class proportions, metrics that matter with imbalanced data (F1-Score vs Accuracy), ROC and Precision-Recall curves, learning curves to diagnose bias/variance, 4-model comparison with CV, and GridSearchCV for hyperparameter optimization.
# Key features
$ K-Fold Cross Validation: 5 folds for robust estimation
$ Stratified K-Fold: maintains class proportion in each fold
$ Advanced metrics: precision, recall, F1-score, ROC-AUC
$ ROC and Precision-Recall curves for imbalanced data
$ Learning curves for bias/variance diagnosis
$ GridSearchCV: hyperparameter search with CV
# Gallery
# Technologies used
