cryptic25glitch/FWI-Predictor

A Ridge Regression project using the Algerian Forest Fires Dataset # FWI Prediction Using Ridge Regression This project uses **Ridge Regression** to predict the **Fire Weather Index (FWI)** from the **Algerian Forest Fires dataset**. The model learns from meteorological and environmental features such as temperature, humidity, wind speed, and drought codes. --- ## Dataset - Source: UCI ML Repository - Total Records: 244 (from two regions in Algeria) - Target: `FWI` (Fire Weather Index) - Features: Temperature, RH, WS, Rain, FFMC, DMC, DC, ISI, etc. --- ## Model - **Model Used**: Ridge Regression (L2 regularized linear regression) - **Scaler**: StandardScaler for feature normalization - **Validation**: K-Fold Cross-Validation - **Tuning**: GridSearchCV for optimal alpha (λ) --- ## Evaluation Metrics - Mean Absolute Error (MAE) - Root Mean Squared Error (RMSE) - R² Score