Interactive Machine Learning via Transparent Modeling: Putting Experts in the Driver’s Seat

In machine learning often a tradeoff must be made between accuracy and intelligibility: the most accurate models usually are not very intelligible (e.g., deep nets, boosted trees, and random forests),