Contrast set mining through subgroup discovery applied to brain Ischaemina data

Petra Kralj, Nada Lavrač, Dragan Gamberger, Antonija Krstǎić

Research output: Contribution to Book/Report typesConference contributionpeer-review

Abstract (may include machine translation)

Contrast set mining aims at finding differences between different groups. This paper shows that a contrast set mining task can be transformed to a subgroup discovery task whose goal is to find descriptions of groups of individuals with unusual distributional characteristics with respect to the given property of interest. The proposed approach to contrast set mining through subgroup discovery was successfully applied to the analysis of records of patients with brain stroke (confirmed by a positive CT test), in contrast with patients with other neurological symptoms and disorders (having normal CT test results). Detection of coexisting risk factors, as well as description of characteristic patient subpopulations are important outcomes of the analysis.

Original languageEnglish
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 11th Pacific-Asia Conference, PAKDD 2007, Proceedings
PublisherSpringer Verlag
Pages579-586
Number of pages8
ISBN (Print)9783540717003
DOIs
StatePublished - 2007
Externally publishedYes
Event11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007 - Nanjing, China
Duration: 22 May 200725 May 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4426 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007
Country/TerritoryChina
CityNanjing
Period22/05/0725/05/07

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