Informative Summarization of Numeric Data

We consider the following data summarization problem. We are given a dataset including ordinal or numeric explanatory attributes and an outcome attribute. We want to produce a summary of how the explanatory attributes affect the outcome attribute. The summary must be human-interpretable, concise, and informative in the sense that it can accurately approximate the distribution of the outcome attribute. We propose a solution that addresses the fundamental challenge of this problem--handling large numeric domains--and we experimentally show the effectiveness and efficiency of our approach on real datasets.