Takes a list of database experiment ID's and creates emulators from that stored data
1 2 3 | create_emulators_from_database_experiments(dblink, parameters, measures,
emulator_list, percent_train = 75, percent_test = 15,
percent_validation = 10, normalise_set = FALSE, experiment_id)
|
dblink |
A link to the database in which this table is being created |
parameters |
The parameters of the simulation that are being analysed |
measures |
The measures of the simulation that are being assessed |
emulator_list |
Vector of the types of emulation model to create. Accepted abbreviations are: SVM (Support-Vector Machine), GP (Gaussian Process Model), NNET (Neural Network), RF (Random Forest), GLM (General Linear Model) |
percent_train |
Percent of the dataset to use as training |
percent_test |
Percent of the dataset to use as testing |
percent_validation |
Percent of the dataset to use as validation |
normalise_set |
Whether data retrieved from the database should be normalised |
experiment_id |
List of experiment IDs in the database that form the test, training, and validation sets |
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