Subgroup discovery techniques and applications

11Citations
Citations of this article
17Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This paper presents the advances in subgroup discovery and the ways to use subgroup discovery to generate actionable knowledge for decision support. Actionable knowledge is explicit symbolic knowledge, typically presented in the form of rules, that allow the decision maker to recognize some important relations and to perform an appropriate action, such as planning a population screening campaign aimed at detecting individuals with high disease risk. Two case studies from medicine and functional genomics are used to present the lessons learned in solving problems requiring actionable knowledge generation for decision support. © Springer-Verlag Berlin Heidelberg 2005.

Cite

CITATION STYLE

APA

Lavrač, N. (2005). Subgroup discovery techniques and applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3518 LNAI, pp. 2–14). Springer Verlag. https://doi.org/10.1007/11430919_2

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free