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Descriptive Subgroup Mining of Folk Music Host Publication: SECOND INTERNATIONAL WORKSHOP ON MACHINE LEARNING AND MUSIC AT ECML PKDD Authors: J. Taminau, R. Hillewaere, S. Meganck, D. Conklin, A. Nowé and B. Manderick Publication Year: 2009 Number of Pages: 6
Abstract: Descriptive analysis of music corpora is important to musicologists who are interested in identifying the properties that characterize
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 result in the form of a collection of sim-
ple rules. Classifcation accuracy is not the goal of this study. Instead, we
discuss some of the highest scoring rules with respect to their descriptive
power.
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