CSM-SD: Methodology for contrast set mining through subgroup discovery

Authors:
Petra Kralj Novak;Nada Lavrač;Dragan Gamberger;Antonija Krstačić
Affiliations:
Department of Knowledge Technologies, Joef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia;Department of Knowledge Technologies, Joef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia and University of Nova Gorica, Vipavska 13, 5000 Nova Gorica, Slovenia;Rudjer Bošković Institute, Bijenička 54, 10000 Zagreb, Croatia;University Hospital of Traumatology, Draškovićeva 19, 10000 Zagreb, Croatia
Venue:
Journal of Biomedical Informatics
Year:
2009

Citing 18
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Abstract

This paper addresses a data analysis task, known as contrast set mining, whose goal is to find differences between contrasting groups. As a methodological novelty, it is shown that this task can be effectively solved by transforming it to a more common and well-understood subgroup discovery task. The transformation is studied in two learning settings, a one-versus-all and a pairwise contrast set mining setting, uncovering the conditions for each of the two choices. Moreover, the paper shows that the explanatory potential of discovered contrast sets can be improved by offering additional contrast set descriptors, called the supporting factors. The proposed methodology has been applied to uncover distinguishing characteristics of two groups of brain stroke patients, both with rapidly developing loss of brain function due to ischemia:those with ischemia caused by thrombosis and by embolism, respectively.