Type: Package
Package: innsight
Title: Get the Insights of your Neural Network
Version: 0.1.1
Authors@R: 
    c(person(given = "Niklas",
             family = "Koenen",
             role = c("aut", "cre"),
             email = "niklas.koenen@gmail.com",
             comment = c(ORCID = "0000-0002-4623-8271")),
      person(given = "Raphael",
             family = "Baudeu",
             role = "ctb",
             email = "raphael.baudeu@gmail.com"))
Description: Interpretability methods to analyze the behavior and
    individual predictions of modern neural networks. Implemented methods
    are: 'Connection Weights' described by Olden et al. (2004)
    <doi:10.1016/j.ecolmodel.2004.03.013>, Layer-wise Relevance
    Propagation ('LRP') described by Bach et al. (2015)
    <doi:10.1371/journal.pone.0130140>, Deep Learning Important Features
    ('DeepLIFT') described by Shrikumar et al.  (2017) <arXiv:1704.02685>
    and gradient-based methods like 'SmoothGrad' described by Smilkov et
    al. (2017) <arXiv:1706.03825>, 'Gradient x Input' described by
    Baehrens et al. (2009) <arXiv:0912.1128> or 'Vanilla Gradient'.
License: MIT + file LICENSE
URL: https://bips-hb.github.io/innsight/,
        https://github.com/bips-hb/innsight/
BugReports: https://github.com/bips-hb/innsight/issues/
Depends: R (>= 3.5.0)
Imports: checkmate, ggplot2, R6, torch
Suggests: covr, keras, knitr, neuralnet, plotly, rmarkdown, tensorflow,
        testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
RoxygenNote: 7.2.1
Collate: 'ConnectionWeights.R' 'Convert_keras.R' 'Convert_neuralnet.R'
        'Convert_torch.R' 'Converter.R' 'DeepLift.R' 'GradienBased.R'
        'InterpretingLayer.R' 'InterpretingMethod.R' 'LRP.R'
        'Layer_conv1d.R' 'Layer_conv2d.R' 'Layer_dense.R'
        'Layer_other.R' 'Layer_pooling.R' 'innsight.R' 'utils.R'
NeedsCompilation: no
Packaged: 2022-08-29 14:49:57 UTC; niklas
Author: Niklas Koenen [aut, cre] (<https://orcid.org/0000-0002-4623-8271>),
  Raphael Baudeu [ctb]
Maintainer: Niklas Koenen <niklas.koenen@gmail.com>
Repository: CRAN
Date/Publication: 2022-08-29 15:10:02 UTC
