Adapting classification rule induction to subgroup discovery

N Lavrac, PA Flach, B Kavsek, L Todorovski

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

23 Citations (Scopus)


Rule learning is typically used for solving classification and prediction tasks. However, learning of classification rules can be adapted also to subgroup discovery. This paper shows how this can be achieved by modifying the covering algorithm and the search heuristic, performing probabilistic classification of instances, and using an appropriate measure for evaluating the results of subgroup discovery. Experimental evaluation of the CN2-SD subgroup discovery algorithm on 17 UCI data sets demonstrates substantial reduction of the number of induced rules, increased rule coverage and rule significance, as well as slight improvements in terms of the area under the ROC curve.
Translated title of the contributionAdapting classification rule induction to subgroup discovery
Original languageEnglish
Title of host publicationUnknown
EditorsV. Kumar et al.
PublisherIEEE Computer Society
Pages266 - 273
Number of pages7
ISBN (Print)0769517544
Publication statusPublished - Dec 2002

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the 2002 IEEE International Conference on Data Mining


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