Machine Learning and Mapping for Spatial Epidemiology

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Documentation for package ‘mlspatial’ version 0.1.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

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 Global variables used in evaluation functions
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
pancre_mort	Pancreatic Cancer Mortality Data
panc_incidence	Pancreatic Cancer Incidence Data
panc_prevalence	Pancreatic Cancer Prevalence 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