Informative Summarization of Numeric Data
Proceedings of the 31st International Conference on Scientific and Statistical Database Management(2019)
摘要
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.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络