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Package: nn2poly
Title: Neural Network Weights Transformation into Polynomial Coefficients
Version: 0.1.3
Authors@R: c(
person(given = "Pablo", family = "Morala", role = c("aut", "cre"),
email = "moralapablo@gmail.com",
comment = c(ORCID = "0000-0002-4109-2330")),
person(given = "Iñaki", family = "Ucar", role = c("aut"),
email = "iucar@fedoraproject.org",
comment = c(ORCID = "0000-0001-6403-5550")),
person(given = "Jose Ignacio", family = "Diez", role = c("ctr"))
)
Description: Implements a method that builds the coefficients of a polynomial
model that performs almost equivalently as a given neural network
(densely connected). This is achieved using Taylor expansion at the
activation functions. The obtained polynomial coefficients can be used
to explain features (and their interactions) importance in the neural network,
therefore working as a tool for interpretability or eXplainable Artificial
Intelligence (XAI). See Morala et al. 2021 <doi:10.1016/j.neunet.2021.04.036>,
and 2023 <doi:10.1109/TNNLS.2023.3330328>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports:
Rcpp,
generics,
matrixStats,
pracma
Suggests:
keras, tensorflow, reticulate,
luz, torch,
cowplot, ggplot2, patchwork,
testthat (>= 3.0.0), vdiffr,
knitr, rmarkdown
LinkingTo:
Rcpp,
RcppArmadillo
VignetteBuilder: knitr
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Config/testthat/edition: 3
URL: https://ibidat.github.io/nn2poly/, https://github.com/IBiDat/nn2poly
BugReports: https://github.com/IBiDat/nn2poly/issues