Man pages for mlspatial
Machine Learning and Mapping for Spatial Epidemiology
| africa_shp | Africa shapefile data |
| africa_shps | Africa shapefile data 2 |
| compute_spatial_autocorr | Compute Moran's I & LISA, classify clusters |
| eval_model | Get RMSE/MAE/R² metrics on training data |
| global_variables_eval | Declare known global variables to suppress R CMD check NOTE... |
| join_data | Join spatial and incidence datasets |
| load_incidence_data | Load incidence data from Excel |
| load_shapefile | Load shapefile as sf + optionally convert to sp |
| model_evaluation_examples | Examples for model evaluation functions |
| panc_incidence | Pancreatic Cancer Incidence Data |
| panc_prevalence | Pancreatic Cancer Prevalence Data |
| pancre_mort | Pancreatic Cancer Mortality Data |
| plot_map_grid | Arrange Multiple tmap Plots in a Grid |
| plot_obs_vs_pred | Plot observed vs predicted values with correlation |
| plot_single_map | Build a tmap for a single variable |
| train_rf | Train Random Forest model |
| train_svr | Train Support Vector Regression (SVR) model |
| train_xgb | Train XGBoost model |
