createAndEvaluateFolds: Create and evaluate folds within k-fold cross validation

In spartan: Simulation Parameter Analysis R Toolkit ApplicatioN: 'spartan'

Description

Create and evaluate folds within k-fold cross validation

Usage

createAndEvaluateFolds(fold_size, test_fold_start, test_fold_end, dataset,
  network_struc, formula, parameters, measures, algorithm_settings)

Arguments

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

Value

MSE errors for all network structures

spartan documentation built on May 2, 2019, 9:39 a.m.