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>.