Package: nn2poly 1.0.1.9000

Pablo Morala

nn2poly: Neural Network Weights Transformation into Polynomial Coefficients

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>.

Authors:Pablo Morala [aut, cre], Iñaki Ucar [aut], Jose Ignacio Diez [ctr]

nn2poly_1.0.1.9000.tar.gz
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nn2poly_1.0.1.9000.tgz(r-4.6-x86_64)nn2poly_1.0.1.9000.tgz(r-4.6-arm64)nn2poly_1.0.1.9000.tgz(r-4.5-x86_64)nn2poly_1.0.1.9000.tgz(r-4.5-arm64)
nn2poly_1.0.1.9000.tar.gz(r-4.7-arm64)nn2poly_1.0.1.9000.tar.gz(r-4.7-x86_64)nn2poly_1.0.1.9000.tar.gz(r-4.6-arm64)nn2poly_1.0.1.9000.tar.gz(r-4.6-x86_64)
nn2poly_1.0.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
nn2poly/json (API)

# Install 'nn2poly' in R:
install.packages('nn2poly', repos = c('https://ibidat.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ibidat/nn2poly/issues

Pkgdown/docs site:https://ibidat.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

6.73 score 12 stars 30 scripts 371 downloads 4 exports 3 dependencies

Last updated from:c09b74b592. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK171
linux-devel-x86_64OK178
source / vignettesOK233
linux-release-arm64OK159
linux-release-x86_64OK188
macos-release-arm64OK174
macos-release-x86_64OK344
macos-oldrel-arm64OK229
macos-oldrel-x86_64OK488
windows-devel-arm64OK367
windows-devel-x86_64OK172
windows-release-arm64OK370
windows-release-x86_64OK134
windows-oldrel-x86_64OK139
wasm-releaseOK139

Exports:add_constraintsfitluz_model_sequentialnn2poly

Dependencies:genericsRcppRcppArmadillo

Classification example using tensorflow
Multiclass classification example | Data preparation | Neural network | Build and train the NN | NN Predictions | Polynomial representation | Using nn2poly | Obtaining polynomial predictions | Visualizing the results

Last update: 2026-07-16
Started: 2024-01-15

Introduction to nn2poly
nn2poly package goal | This vignette: a first example | Polynomial structure in nn2poly | Simulated data | Original neural network | Building the needed input for default nn2poly | Polynomial obtained with nn2poly from weights and activation functions | Predictions using the obtained polynomial | Visualizing the results

Last update: 2026-07-16
Started: 2022-01-15

Supported DL frameworks
Data generation | Supported frameworks examples | keras/tensorflow | Model definition | Training | NN predictions | Using nn2poly | luz/torch | Data loader for torch

Last update: 2026-07-16
Started: 2024-01-15