XAI-Bench
Introduced by Liu et al. in Synthetic Benchmarks for Scientific Research in Explainable Machine Learning
XAI-Bench is a suite of synthetic datasets along with a library for benchmarking feature attribution algorithms. Unlike real-world datasets, synthetic datasets allow the efficient computation of conditional expected values that are needed to evaluate ground-truth Shapley values and other metrics. The synthetic datasets released offer a wide variety of parameters that can be configured to simulate real-world data.
Papers
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