The Effect of Feature Selection on Music Genre Classification

  • I Nyoman Yusha Tresnatama Giri Universitas Udayana
  • Luh Arida Ayu Rahning Putri Universitas Udayana

Abstract

One of the things that affects classification results is the correlation of features to the class of a data. This research was conducted to determine the effect of the reduction of features (independent variable) that have the weakest correlation or have a distant relationship with the class (dependent variable). Bivariate Pearson Correlation is used as a feature selection method and K-Nearest Neighbor is used as a classification method. Results of the test showing that, 75.1% average accuracy was obtained for classification without feature selection, while using feature selection, average accuracy was obtained in the range of 75% - 79.3%. The average accuracy obtained by the selection of features tends to be higher compared to the accuracy obtained without selection of features.

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Published
2021-05-29
How to Cite
GIRI, I Nyoman Yusha Tresnatama; PUTRI, Luh Arida Ayu Rahning. The Effect of Feature Selection on Music Genre Classification. JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 9, n. 4, p. 549-554, may 2021. ISSN 2654-5101. Available at: <https://ojs.unud.ac.id/index.php/jlk/article/view/64437>. Date accessed: 29 mar. 2024. doi: https://doi.org/10.24843/JLK.2021.v09.i04.p13.