CombineSens {NeuralSens} | R Documentation |
Sensitivity analysis plot over time of the data
Description
Plot of sensitivity of the neural network output respect to the inputs over the time variable from the data provided
Usage
CombineSens(object, comb_type = "mean")
Arguments
object |
|
comb_type |
Function to combine the matrixes of the |
Value
SensMLP
object with the sensitivities combined
Examples
fdata <- iris
## Parameters of the NNET ------------------------------------------------------
hidden_neurons <- 5
iters <- 250
decay <- 0.1
#' ## TRAIN nnet NNET --------------------------------------------------------
# Create a formula to train NNET
form <- paste(names(fdata)[1:ncol(fdata)-1], collapse = " + ")
form <- formula(paste(names(fdata)[5], form, sep = " ~ "))
set.seed(150)
mod <- nnet::nnet(form,
data = fdata,
linear.output = TRUE,
size = hidden_neurons,
decay = decay,
maxit = iters)
# mod should be a neural network classification model
sens <- SensAnalysisMLP(mod, trData = fdata, output_name = 'Species')
combinesens <- CombineSens(sens, "sqmean")
[Package NeuralSens version 1.1.3 Index]