There’s lots of work in the field of machine learning on researching algorithms to create powerful predictive models. In some industries, however, adoption of these algorithms has been slow due to a variety of reasons including, model trust, lack of understanding, and governmental regulations. To help address the adoption issue, researchers have worked in the field of explaining model predictions.

On Tuesday, March 5, Senior Machine Learning Developer, Ralph Abbey, PhD from SAS came to talk about the steps of a research and development project on model-agnostic methods for explanations of predictive models.