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nn2poly
View on CRAN: Click
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Download and install nn2poly package within the R console
Install from CRAN:
install.packages("nn2poly")
Install from Github:
library("remotes")
install_github("cran/nn2poly") Install by package version:
library("remotes")
install_version("nn2poly", "0.1.3") Attach the package and use:
library("nn2poly")
Maintained by
Pablo Morala
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-01-24
Latest Update: 2024-11-11
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 ,
and 2023 .
How to cite:
Pablo Morala (2024). nn2poly: Neural Network Weights Transformation into Polynomial Coefficients. R package version 0.1.3, https://cran.r-project.org/web/packages/nn2poly. Accessed 26 Aug. 2026.
Previous versions and publish date:
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Complete documentation for nn2poly
Functions, R codes and Examples using
the nn2poly R package
Some associated functions: add_constraints . eval_poly . luz_model_sequential . nn2poly . plot.nn2poly . plot_diagonal . plot_taylor_and_activation_potentials . predict.nn2poly . reexports .
Some associated R codes: RcppExports.R . callback.R . constraints.R . constraints_torch.R . eval_poly.R . helpers.R . nn2poly.R . nn2poly_algorithm.R . nn2poly_methods.R . parameters.R . plot_diagonal.R . plot_taylor_and_activation_potentials.R . utils.R . Full nn2poly package functions and examples
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