Package: innsight 0.3.0

innsight: Get the Insights of Your Neural Network

Interpretation methods for analyzing the behavior and individual predictions of modern neural networks in a three-step procedure: Converting the model, running the interpretation method, and visualizing the results. Implemented methods are, e.g., 'Connection Weights' described by Olden et al. (2004) <doi:10.1016/j.ecolmodel.2004.03.013>, layer-wise relevance propagation ('LRP') described by Bach et al. (2015) <doi:10.1371/journal.pone.0130140>, deep learning important features ('DeepLIFT') described by Shrikumar et al. (2017) <arxiv:1704.02685> and gradient-based methods like 'SmoothGrad' described by Smilkov et al. (2017) <arxiv:1706.03825>, 'Gradient x Input' described by Baehrens et al. (2009) <arxiv:0912.1128> or 'Vanilla Gradient'.

Authors:Niklas Koenen [aut, cre], Raphael Baudeu [ctb]