Haiubabdelkader99/water-pump-predictor

Prediction of the functional status of water pumps in Tanzania — a Machine Learning project using Random Forest (DrivenData) # 💧 Water Pump Predictor - Tanzania **Machine Learning app to predict the operational status of water pumps in Tanzania**, based on the DrivenData "Pump It Up" challenge. --- ## Project Overview / Descripción del Proyecto ## 📌 Project Overview This app uses a trained `Random Forest` model to classify water pumps as: - ✅ `functional` - ⚠️ `functional needs repair` - ❌ `non functional` It features a full ML pipeline, from preprocessing to prediction, live evaluation and interactive dashboards. --- ## Final Score / Resultado Final ## 🚀 Try it Online You can test the live app hosted on **Streamlit Cloud**: --- ## 🧠 Model & Techniques Used - RandomForestClassifier (Scikit-learn) - KNNImputer for missing values - TargetEncoder for categorical variables - LabelEncoder for final mapping - Feature importance visualization - Geo-mapping with Pydeck --- ## 🧭 App Functionalities ### 🔍 1. Prediction Mode - Upload a test dataset (`Testsetvalues.csv`) - Predict status using the trained model - Download enriched CSV with predictions - Interactive prediction map ### 📊 2. Evaluation Mode - Upload training and label datasets - Shows classification report + confusion matrix - Validates the model's performance on full data ### 📈 3. Interactive Dashboard - Upload prediction results (`predictions_full.csv`) - Filter by `region`, `status`, or `construction_year` - Explore data visually + map filtered results --- ## 🗂️ Project Structure ``` 📁 water-pump-predictor/ ├── app_v4_final.py # Streamlit App (v4 with all features) ├── model_rf.joblib # Trained RandomForest model ├── target_encoder.joblib # Encoder for categorical vars ├── knn_imputer.joblib # Fitted KNN imputer ├── final_columns.joblib # Ordered feature columns ├── Trainingsetvalues.csv # Training data ├── Trainginsetlabels.csv # Labels for training data ├── Testsetvalues.csv # Data to predict ├── predictions_full.csv …