Reference

Specifying the ensemble Functions for specifying how to create the ensemble.
setEnsembleFromDesign()	Create setting for creating ensemble from model settings
setEnsembleFromResults()	Create setting for creating ensemble from model settings
setEnsembleFromFiles()	Create setting for creating ensemble from model settings
Filter functions Functions for filtering base level models.
filterBaseModels()	Filter our base level 1 models that do not perform sufficiently well
Different combiners Functions combining based models (e.g., fusion or stacking).
createFusionCombiner()	Create the settings for a fusion ensemble
createStackerCombiner()	Create the settings for a stacker ensemble - this is an emsemble that learns how to combine level 1 models using labelled data
Creating the ensemble Functions creating an ensemble model and then applying it to make predictions.
runEnsemble()	Code to run the ensemble model development
applyEnsemble()	Apply an ensembleModel to new data
applyEnsembleToPredictions()	Apply an ensembleModel to list of base model prediction objects
Saving/loading the ensemble Functions for saving/loading an ensemble model or result
saveEnsemble()	Save an ensemble result
loadEnsemble()	Load a previously saved ensemble result
saveEnsembleModel()	Save an ensemble model (object of class ensembleModel)
loadEnsembleModel()	Load a previously saved ensemble model (object of class ensembleModel)
EnsemblePatientLevelPrediction The package name
EnsemblePatientLevelPrediction	EnsemblePatientLevelPrediction