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FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems

Sokol, Kacper; Hepburn, Alexander; Poyiadzi, Rafael; Clifford, Matthew; Santos-Rodriguez, Raul; Flach, Peter


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  <dc:creator>Sokol, Kacper</dc:creator>
  <dc:creator>Hepburn, Alexander</dc:creator>
  <dc:creator>Poyiadzi, Rafael</dc:creator>
  <dc:creator>Clifford, Matthew</dc:creator>
  <dc:creator>Santos-Rodriguez, Raul</dc:creator>
  <dc:creator>Flach, Peter</dc:creator>
  <dc:date>2020-05-19</dc:date>
  <dc:description>FAT Forensics is a Python toolbox for evaluating fairness, accountability and transparency of predictive systems. It is built on top of SciPy and NumPy, and is distributed under the 3-Clause BSD license (new BSD).</dc:description>
  <dc:identifier>https://zenodo.org/record/3833199</dc:identifier>
  <dc:identifier>10.5281/zenodo.3833199</dc:identifier>
  <dc:identifier>oai:zenodo.org:3833199</dc:identifier>
  <dc:relation>url:https://github.com/fat-forensics/fat-forensics/tree/0.1.0</dc:relation>
  <dc:relation>doi:10.21105/joss.01904</dc:relation>
  <dc:relation>arxiv:arXiv:1909.05167</dc:relation>
  <dc:relation>doi:10.5281/zenodo.3833198</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:source>The Journal of Open Source Software</dc:source>
  <dc:subject>Fairness</dc:subject>
  <dc:subject>Accountability</dc:subject>
  <dc:subject>Transparency</dc:subject>
  <dc:subject>Artificial Intelligence</dc:subject>
  <dc:subject>Machine Learning</dc:subject>
  <dc:subject>Software</dc:subject>
  <dc:subject>Python Toolbox</dc:subject>
  <dc:title>FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>software</dc:type>
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