Toward Explainable Machine Learning: Interactive Interfaces for Model Interpretation

This paper surveys and evaluates interactive techniques for explaining machine learning model decisions to non-expert users. We propose a taxonomy of explanation interfaces and validate them through a user study with domain experts.