yuntech-bdrc/WaterQuality
An explainable water quality classification model
Leverages XGBoost for binary water potability and multi-class quality classification, achieving 96% accuracy on quality datasets. SHAP and TreeSHAP provide feature-level interpretability to explain individual predictions. Includes evaluation on public Kaggle water datasets with metrics across accuracy, precision, recall, and F1-score.
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May 23, 2025
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