Description Usage Arguments Value
Create and evaluate folds within k-fold cross validation
1 2 | createAndEvaluateFolds(fold_size, test_fold_start, test_fold_end, dataset,
network_struc, formula, parameters, measures, algorithm_settings)
|
fold_size |
Number of rows of the dataset that form each fold |
test_fold_start |
Starting position of the training or test fold in the dataset |
test_fold_end |
End position of the training or test fold in the dataset |
dataset |
Dataset for which the training and test folds are being developed |
network_struc |
Network structure for which the folds are being assessed |
formula |
Parameters and measures formula to use in creating the network |
parameters |
Names of the parameters that form the input nodes of the neural network |
measures |
Names of the simulation responses that form the output node of the neural network |
algorithm_settings |
Object output from the function emulation_algorithm_settings, containing the settings of the machine learning algorithms to use in emulation creation. In this case, the settings parameter we are interested in is number of generations |
MSE errors for all network structures
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