Internal function to create the ensemble
create_ensemble(ensemble_emulations, all_emulator_predictions,
emulator_test_data, measures, emulator_types, pre_normed_mins,
pre_normed_maxes, algorithm_settings = NULL, normalise = FALSE,
timepoint = NULL, output_formats = c("pdf"))All emulations to build into the ensemble
Test set predictions from all emulators, on which the ensemble will be trained / emulators weighted
Data on which the ensemble performance will be assessed
Simulation responses the model should predict
Machine learning techniques being employed
The minimum values of each parameter prior to data normalisation. Used to rescale the results
The maximum values of each parameter prior to data normalisation. Used to rescale the results
Object output from the function emulation_algorithm_settings, containing the settings of the machine learning algorithms to use in emulation creation. Used here to obtain settings relevant to ensemble creation - namely number of generations and whether the ensemble should be saved to file, as well as whether plots should be produced showing ensemble performance.
Whether the predictions generated when testing the ensemble should be normalised for presenting test results
Simulation timepoint for which an ensemble is being created
File formats in which result graphs should be produced
Generated ensemble object