Auditing Black-box Models for Indirect Influence

23 Feb 2016Philip AdlerCasey FalkSorelle A. FriedlerGabriel RybeckCarlos ScheideggerBrandon SmithSuresh Venkatasubramanian

Data-trained predictive models see widespread use, but for the most part they are used as black boxes which output a prediction or score. It is therefore hard to acquire a deeper understanding of model behavior, and in particular how different features influence the model prediction... (read more)

PDF Abstract

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet