Package: NeuralSens
Version: 1.1.3
Title: Sensitivity Analysis of Neural Networks
Description: Analysis functions to quantify inputs importance in neural network models.
  Functions are available for calculating and plotting the inputs importance and obtaining
  the activation function of each neuron layer and its derivatives. The importance of a given
  input is defined as the distribution of the derivatives of the output with respect to that
  input in each training data point <doi:10.18637/jss.v102.i07>.
Author: José Portela González [aut],
  Antonio Muñoz San Roque [aut],
  Jaime Pizarroso Gonzalo [aut, ctb, cre]
Maintainer: Jaime Pizarroso Gonzalo <jpizarroso@comillas.edu>
Imports: ggplot2, gridExtra, NeuralNetTools, reshape2, caret,
        fastDummies, stringr, Hmisc, ggforce, scales, ggnewscale,
        magrittr, ggrepel, ggbreak, dplyr
Suggests: h2o, RSNNS, nnet, neuralnet, plotly, e1071
RoxygenNote: 7.3.1
NeedsCompilation: no
URL: https://github.com/JaiPizGon/NeuralSens
BugReports: https://github.com/JaiPizGon/NeuralSens/issues
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Authors@R: c(
    person(given = "José", family = "Portela González",
      email = "Jose.Portela@iit.comillas.edu", role = "aut"),
	person(given = "Antonio", family = "Muñoz San Roque",
      email = "antonio.munoz@iit.comillas.edu", role = "aut"),
    person(given = "Jaime", family = "Pizarroso Gonzalo",
      email = "jpizarroso@comillas.edu", role = c("aut","ctb", "cre"))
    )
Packaged: 2024-05-11 19:26:10 UTC; jpizarroso
Repository: CRAN
Date/Publication: 2024-05-11 19:43:03 UTC
Built: R 4.6.0; ; 2026-04-30 14:30:16 UTC; unix
