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"What and How of Machine Learning Transparency: Building Bespoke ..."

Kacper Sokol et al. (2022)

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DOI: 10.48550/ARXIV.2209.03813

access: open

type: Informal or Other Publication

metadata version: 2023-03-21

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  - journals/corr/abs-2209-03813
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  - https://dblp.org/rec/journals/corr/abs-2209-03813
Kacper Sokol, Alexander Hepburn, Raúl Santos-Rodríguez, Peter A. Flach:
What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components. CoRR abs/2209.03813 (2022)

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