Ngum12/linear_regression_model

Building a linear regression model that addresses Conflict risk and Peacebuilding in any nation in Africa # Predicting African Conflict Risk: An ML-Powered Early Warning System ## 🎯 Project Mission To develop an innovative early warning system that predicts potential conflict zones in African regions using machine learning, providing actionable insights for peacekeeping organizations and humanitarian agencies. → Alternatively, Access Dataset from my Googledrive if you donot have a Kaggle account Documentation ## 📊 Project Overview This project combines machine learning, API development, and mobile technology to create a practical tool for conflict prediction and prevention. Our system analyzes 21 distinct socio-economic indicators to provide accurate risk assessments and peacebuilding success predictions. github.com ### Key Achievements - **96.26%** accuracy in conflict risk prediction - **97.28%** accuracy in peacebuilding success prediction - Real-time predictions via RESTful API - Cross-platform mobile application for field deployment ## 🔬 Technical Components ### 1. Machine Learning Model Our predictive model leverages a comprehensive dataset of African socio-economic indicators: #### Dataset Specifications - **Records**: 9,072 entries - **Features**: 21 indicators including: - Poverty rates - Political stability indices - Educational metrics - Resource distribution - Demographic patterns #### Model Performance | Model Type | R² Score | RMSE | Application | |------------|----------|------|-------------| | Random Forest | 0.9626 | 0.6452 | Conflict Risk | | Random Forest | 0.9728 | 2.2516 | Peacebuilding | → View Full Model Documentation NOTEBOOK ### 2. FastAPI Implementation Our API provides real-time prediction capabilities with robust input validation: ```python POST /predict ``` #### Features - Comprehensive input validation - Cross-Origin Resource Sharing (CORS) enabled - Swagger UI documentation - Production deployment on …