Towards more collaboration between machine learning systems and their users
This article investigates a way to deepen collaboration between Machine Learning Systems (MLS) and their users through the generation of explanations. More precisely, it focuses on the advises that may be given for helping the user during the evaluation of the MLS results and their correction. This is illustrated through the system EILP, an explanatory interface that supports the user during these tasks.
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