Abstract (may include machine translation)
The goal of exploratory pattern mining is to find patterns that exhibit yet unknown relationships in data and to provide insightful representations of detected relationships. This paper explores contrast set mining and an approach to improving its explanatory potential by using the so called supporting factors that provide additional descriptions of the detected patterns. The proposed methodology is described in a medical data analysis problem of distinguishing between similar diseases in the analysis of patients suffering from brain ischaemia.
Original language | English |
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Pages (from-to) | 157-161 |
Number of pages | 5 |
Journal | IFMBE Proceedings |
Volume | 16 |
Issue number | 1 |
State | Published - 2007 |
Externally published | Yes |
Event | 11th Mediterranean Conference on Medical and Biological Engineering and Computing, MEDICON 2007 - Ljubljana, Slovenia Duration: 26 Jun 2007 → 30 Jun 2007 |
Keywords
- Brain ischaemia
- Contrast set mining
- Exploratory data analysis
- Subgroup discovery
- Supporting factors