Web: http://arxiv.org/abs/1909.12367

Sept. 23, 2022, 1:12 a.m. | Jinsung Yoon, Sercan O. Arik, Tomas Pfister

cs.LG updates on arXiv.org arxiv.org

Understanding black-box machine learning models is crucial for their
widespread adoption. Learning globally interpretable models is one approach,
but achieving high performance with them is challenging. An alternative
approach is to explain individual predictions using locally interpretable
models. For locally interpretable modeling, various methods have been proposed
and indeed commonly used, but they suffer from low fidelity, i.e. their
explanations do not approximate the predictions well. In this paper, our goal
is to push the state-of-the-art in high-fidelity locally interpretable …

arxiv modeling

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