Martijn Witjes

Workshop room 1 - C221 Theoretical background for machine learning and python implementations Integrating raster data with scikit-learn models Why use pyeumap.LandMapper? Spatial overlay to prepare the training samples Spatial cross-validation to evaluate the ML model performance Hyperparameter optimization to tune the ML model Fitting the final ML model Generating spatial predictions using the fitted model Theoretical background for Ensemble ML and python implementations General concepts and main advantages of spatiotemporal machine learning Why use LandMapper? Spacetime overlay to prepare the training samples Spacetime cross-validation to evaluate the EML model performance Hyperparameter optimization to tune the EML model Fitting the final EML model Generating spatial predictions using the fitted model