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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) <doi:10.48550/arXiv.1704.02685> and gradient-based methods like 'SmoothGrad' described by Smilkov et al. (2017) <doi:10.48550/arXiv.1706.03825>, 'Gradient x Input' described by Baehrens et al. (2009) <doi:10.48550/arXiv.0912.1128> or 'Vanilla Gradient'.
Version: | 0.3.0 |
Depends: | R (≥ 3.5.0) |
Imports: | checkmate, cli, ggplot2, methods, R6, torch |
Suggests: | covr, fastshap, GGally, grid, gridExtra, gtable, keras, knitr, lime, luz, neuralnet, palmerpenguins, plotly, rmarkdown, ranger, spelling, tensorflow, testthat (≥ 3.0.0) |
Published: | 2023-12-21 |
DOI: | 10.32614/CRAN.package.innsight |
Author: | Niklas Koenen [aut, cre], Raphael Baudeu [ctb] |
Maintainer: | Niklas Koenen <niklas.koenen at gmail.com> |
BugReports: | https://github.com/bips-hb/innsight/issues/ |
License: | MIT + file LICENSE |
URL: | https://bips-hb.github.io/innsight/, https://github.com/bips-hb/innsight/ |
NeedsCompilation: | no |
Language: | en-US |
Materials: | README NEWS |
CRAN checks: | innsight results |
Reference manual: | innsight.pdf |
Vignettes: |
Example 1: Iris dataset with torch Example 2: Penguin dataset with torch and luz In-depth explanation Introduction to innsight |
Package source: | innsight_0.3.0.tar.gz |
Windows binaries: | r-devel: innsight_0.3.0.zip, r-release: innsight_0.3.0.zip, r-oldrel: innsight_0.3.0.zip |
macOS binaries: | r-release (arm64): innsight_0.3.0.tgz, r-oldrel (arm64): innsight_0.3.0.tgz, r-release (x86_64): innsight_0.3.0.tgz, r-oldrel (x86_64): innsight_0.3.0.tgz |
Old sources: | innsight archive |
Please use the canonical form https://CRAN.R-project.org/package=innsight to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.