Expert-Guided Subgroup Discovery: Methodology and Application
arXiv:1106.4576 · doi:10.1613/jair.1089
Abstract
This paper presents an approach to expert-guided subgroup discovery. The main step of the subgroup discovery process, the induction of subgroup descriptions, is performed by a heuristic beam search algorithm, using a novel parametrized definition of rule quality which is analyzed in detail. The other important steps of the proposed subgroup discovery process are the detection of statistically significant properties of selected subgroups and subgroup visualization: statistically significant properties are used to enrich the descriptions of induced subgroups, while the visualization shows subgroup properties in the form of distributions of the numbers of examples in the subgroups. The approach is illustrated by the results obtained for a medical problem of early detection of patient risk groups.
Cited by in corpus (5)
- GuideR: a guided separate-and-conquer rule learning in classification, regression, and survival settings
- A framework for redescription set construction
- Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effect
- Approaches For Multi-View Redescription Mining
- Explaining Anomalies in Groups with Characterizing Subspace Rules