VINE: Visualizing Statistical Interactions in Black Box Models
Abstract
As machine learning becomes more pervasive, there is an urgent need for interpretable explanations of predictive models. Prior work has developed effective methods for visualizing global model behavior, as well as generating local (instance-specific) explanations. However, relatively little work has addressed regional explanations - how groups of similar instances behave in a complex model, and the related issue of visualizing statistical...
Paper Details
Title
VINE: Visualizing Statistical Interactions in Black Box Models
Published Date
Apr 1, 2019
Journal
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Notes
History