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