Wildfire Scale Prediction Using Machine Learning
Regression and neural networks on historical wildfire data
- Modeled wildfire scale using historical meteorological and temporal features.
- Compared linear/tree-based regressors with shallow neural networks; conducted ablations on feature subsets.
- Performed error analysis, calibration checks, and residual diagnostics to refine generalization.
Repo: GitHub
Highlights
- Models: Linear regression, RandomForest/XGBoost, shallow NNs
- Pipeline: Feature engineering, scaling, CV, hyperparameter search
- Metrics: MAE, RMSE, R²; calibration and error slicing