An Explainable ML Approach - Author to Present

Bill Fite will discuss his work in progress paper about the importance of being able to explain machine learning models. He will discuss why explainability is important, who demands it, and how he addresses their needs.

We meet every Friday for a peer-to-peer discussion of a pre-selected machine learning research paper. The paper and discussion is in English. Tuesdays we meet to discuss applied topics.

Intro: One of the major roadblocks in getting ML models into use is the difficulty in explaining how the ML model works to users, management and independent model review personnel. In comparison, statistical models are much easier to explain and a variety of standard statistical tests are available to support model validation.

Paper: Explainable AI: https://1drv.ms/b/s!AmNAlD0KvxQJwdpIfjQyxRAAM9Ngzw