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Benchmarking and Survey of Explanation Methods for Black Box Models
Wednesday Apr 28 2021 14:00 GMT
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Why This Is Interesting

The widespread adoption of black-box models in Artificial Intelligence has enhanced the need for explanation methods to reveal how these obscure models reach specific decisions. Retrieving explanations is fundamental to unveil possible biases and to resolve practical or ethical issues. Nowadays, the literature is full of methods with different explanations. This study shows a visual comparison among explanations and a quantitative benchmarking of various explainers.