Category Archives: Interpretability

Properties of Interpretability

Posted on December 5, 2016 by Jesse Johnson

In my last two posts, I wrote about model interpretability, with the goal of trying to understanding what it means and how to measure it. In the first post, I described the disconnect between our mental models and algorithmic models, … Continue reading →

Posted in Interpretability | 1 Comment

Goals of Interpretability

Posted on November 17, 2016 by Jesse Johnson

In my last post, I looked at the gap that arises when we delegate parts of our thought processes to algorithmic models, rather than incorporating the rules they identify directly into our mental models, like we do with traditional statistics. I … Continue reading →

Posted in Interpretability, Uncategorized | 3 Comments

Interacting with ML Models

Posted on October 26, 2016 by Jesse Johnson

The main difference between data analysis today, compared with a decade or two ago, is the way that we interact with it. Previously, the role of statistics was primarily to extend our mental models by discovering new correlations and causal … Continue reading →

Posted in Interpretability | 7 Comments