gattsu001/Telecom-Churn-Predictor
Predicts which telecom customers are likely to churn with 95% accuracy using engineered features from usage, billing, and support data. Implements Sturges-based binning, one-hot encoding, stratified 80/20 train-test split, and a two-level ensemble pipeline with soft voting. Achieves 94.60% accuracy, 0.8968 AUC, 0.8675 precision, 0.7423 recall.
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Language
Python
License
MIT
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Last pushed
Mar 19, 2026
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