Explaining Deviating Subsets Through Explanation Networks

Antti Ukkonen, Vladimir Dzyuba, Matthijs van Leeuwen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

We propose a novel approach to finding explanations of deviating subsets, often called subgroups. Existing approaches for subgroup discovery rely on various quality measures that nonetheless often fail to find subgroup sets that are diverse, of high quality, and most importantly, provide good explanations of the deviations that occur in the data.
Original languageEnglish
Title of host publicationMachine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part II
EditorsMichelangelo Ceci, Jaakko Hollmén, Ljupco Todorovski, Celine Vens, Saso Dzeroski
Number of pages17
Place of PublicationCham
PublisherSpringer International Publishing AG
Publication date30 Dec 2017
Pages425-441
ISBN (Print)978-3-319-71245-1
ISBN (Electronic)978-3-319-71246-8
DOIs
Publication statusPublished - 30 Dec 2017
MoE publication typeA4 Article in conference proceedings
EventEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - Skopje, Macedonia, The Former Yugoslav Republic of
Duration: 18 Sept 201722 Sept 2017
http://ecmlpkdd2017.ijs.si

Publication series

NameLecture Notes in Artificial Intelligence
PublisherSpringer International Publishing AG
Volume10535
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Fields of Science

  • 113 Computer and information sciences

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