emmagope/Predicting-water-pump-functionality

Participation in DrivenData’s “Pump It Up: Data Mining the Water Table” competition. Classification model to predict functionality status of water pumps in Tanzania. # 💧 Predicting Water Pump Functionality This repository contains my submission for the DrivenData competition “Pump It Up: Data Mining the Water Table”. The goal is to predict the functionality status of water pumps in Tanzania based on various environmental and operational features. ## 🧠 Problem Statement This is a classification task where the target variable is `status_group` with three classes: - `functional` - `non functional` - `functional needs repair` ## 📊 Workflow - Exploratory Data Analysis (EDA) - Feature engineering - Model training (RandomForest, XGBoost, etc.) - Class balancing (SMOTE) - Evaluation with F1-score - Submission to DrivenData ## 🧰 Tools & Technologies - Python (pandas, scikit-learn, matplotlib, seaborn, xgboost) - Jupyter Notebooks ## 🏆 Best score achieved My best private leaderboard score was **0.8176**. ## 📁 Repository structure ```bash notebooks/ # Jupyter notebooks for EDA, modeling, submission data/ # Data files (not included) results/ # Visualizations and submission results