CAPE: Explaining outliers by counterbalancing

Conference Paper

In this demonstration we showcase Cape, a system that explains surprising aggregation outcomes. In contrast to previous work, which relies exclusively on provenance, Cape explains outliers in aggregation queries through related outliers in the opposite direction that provide counterbalance. The foundation of our approach are aggregate regression patterns (ARPs) that describe coarse-grained trends in the data. We define outliers as deviations from such patterns and present an efficient algorithm to find counterbalances explaining outliers. In the demonstration, the audience can run aggregation queries over real world datasets, identify outliers of interest in the result of such queries, and browse the patterns and explanations returned by Cape.

Full Text

Duke Authors

Cited Authors

  • Miao, Z; Zeng, Q; Li, C; Glavic, B; Kennedy, O; Roy, S

Published Date

  • January 1, 2018

Published In

Volume / Issue

  • 12 / 12

Start / End Page

  • 1806 - 1809

Electronic International Standard Serial Number (EISSN)

  • 2150-8097

Digital Object Identifier (DOI)

  • 10.14778/3352063.3352071

Citation Source

  • Scopus