SensMLP {NeuralSens} | R Documentation |
Constructor of the SensMLP Class
Description
Create an object of SensMLP class
Usage
SensMLP(
sens = list(),
raw_sens = list(),
mlp_struct = numeric(),
trData = data.frame(),
coefnames = character(),
output_name = character(),
cv = NULL,
boot = NULL,
boot.alpha = NULL
)
Arguments
sens |
list of sensitivity measures, one data.frame per output neuron
|
raw_sens |
list of sensitivities, one matrix per output neuron
|
mlp_struct |
numeric vector describing the structur of the MLP model
|
trData |
data.frame with the data used to calculate the sensitivities
|
coefnames |
character vector with the name of the predictor(s)
|
output_name |
character vector with the name of the output(s)
|
cv |
list list with critical values of significance for std and mean square.
|
boot |
array bootstrapped sensitivity measures.
|
boot.alpha |
array significance level.
Defaults to NULL . Only available for analyzed caret::train models.
|
Value
SensMLP
object
References
Pizarroso J, Portela J, Muñoz A (2022). NeuralSens: Sensitivity Analysis of
Neural Networks. Journal of Statistical Software, 102(7), 1-36.
[Package
NeuralSens version 1.1.3
Index]