Abstract
Descriptive analysis of music corpora is important to musicologists who are interested in identifying
the properties of specific genres of music. In this study we present such an analysis of a large corpus of
folk tunes, all labeled by their origin. Subgroup Discovery (SD) is a rule learning technique located at
the intersection of predictive and descriptive induction. One of the advantages of using this technique is
the intuitive and interpretable results in the form of simple rules. We briefly discuss some of the highest
scoring rules in our testcase and the use of descriptive rules for classi?cation.
the properties of specific genres of music. In this study we present such an analysis of a large corpus of
folk tunes, all labeled by their origin. Subgroup Discovery (SD) is a rule learning technique located at
the intersection of predictive and descriptive induction. One of the advantages of using this technique is
the intuitive and interpretable results in the form of simple rules. We briefly discuss some of the highest
scoring rules in our testcase and the use of descriptive rules for classi?cation.
| Original language | English |
|---|---|
| Pages (from-to) | 377-379 |
| Number of pages | 3 |
| Journal | Proceedings of the Benelux Conference on Artificial Intelligence |
| Volume | 21 |
| Publication status | Published - 2009 |
| Event | 21st Benelux Conference on Artificial Intelligence - Eindhoven, Netherlands Duration: 29 Oct 2009 → 30 Oct 2009 |
Keywords
- Subgroup Discovery