A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is
We present our approach and result for the MediaEval 2017 Acous-ticBrainz Content-based music genre recognition task. Experimental results show that the best results come from random forest with partial feature selection.dblp:conf/mediaeval/KimC17 fatcat:wycy4ixlxngj3glqib3kmqmvfi