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nn2poly

Neural Network Weights Transformation into Polynomial Coefficients

v0.1.3 · Dec 12, 2025 · MIT + file LICENSE

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>.

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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies Rcpp generics matrixStats pracma nn2poly

Version History

new 0.1.3 Mar 10, 2026
updated 0.1.3 ← 0.1.2 diff Dec 11, 2025
updated 0.1.2 ← 0.1.1 diff Nov 10, 2024
updated 0.1.1 ← 0.1.0 diff Jan 29, 2024
new 0.1.0 Jan 23, 2024