I am working on the design of predictive models that are both accurate and interpretable by a human. These models are built from association rules such as dyspepsia & epigastric pain -> heartburn. Association rules are commonly used in the data mining community for database exploration, but have not been heavily employed in machine learning or statistics for prediction problems. I will present three algorithms for decision lists, where classification is based on a list of rules:
