Saliency cards, developed at MIT and IBM, seek to describe a machine-learning model’s behavior and to help users quickly compare methods so they can choose the right one for their task.
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MIT researchers developed a method that helps a user to better understand a machine-learning model’s reasoning, and how that reasoning compares to that of a human. The technique enables a user to rapidly identify and analyze patterns in a model’s behavior.
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