These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
Shapley Variable Importance Cloud (ShapleyVIC)
Following the VIC framework, our proposed ShapleyVIC extends the widely used Shapley-based variable importance measures beyond final models for a comprehensive assessment and has important practical implications.
References
1. Nikulin, M.S., 2001. Hellinger distance. In Encyclopedia of Mathematics. EMS Press. 2. Hellinger, E., 1909. Neue Begründung der Theorie quadratischer Formen von unendlichvielen Veränderlichen. Journal für die reine und angewandte Mathematik, 136, pp.210–271. 3. Jeffreys, H., 1946. An invariant form for the prior probability in estimation problems. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 186(1007), pp.453–461. 4. Liese, F. and Miescke, K.-J., 2008. Statistical Decision Theory: Estimation, Testing, and Selection. Springer. 5. Pardo, L., 2006. Statistical Inference Based on Divergence Measures. Chapman and Hall/CRC.
About the metric
You can click on the links to see the associated metrics
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