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Lecture Notes in Computer Science
The aim of this paper is to investigate music genre recognition in the rough set-based environment. Experiments involve a parameterized music database containing 1100 music excerpts. The database is divided into 11 classes corresponding to music genres. Tests are conducted using the Rough Set Exploration System (RSES), a toolset for analyzing data with the use of methods based on the rough set theory. Classification effectiveness employing rough sets is compared against k-Nearest Neighborsdoi:10.1007/978-3-319-19941-2_36 fatcat:xgarfliqmbevlmxtcfmuyqheyi